Compositions and methods for identifying nucleic acid molecules

ABSTRACT

The present disclosure provides methods and compositions for sequencing nucleic acid molecules and identifying individual sample nucleic acid molecules using Molecular Index Tags (MITs). Furthermore, reaction mixtures, kits, and adapter libraries are provided.

RELATED APPLICATIONS

This application is a divisional of U.S. Utility application Ser. No.15/372,279, filed Dec. 7, 2016, now U.S. Pat. No. 10,011,870. Theentirety of this application is hereby incorporated herein by referencefor the teachings therein.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has beensubmitted electronically in ASCII format and is hereby incorporated byreference in its entirety. Said ASCII copy, created on Nov. 14, 2017, isnamed N_018_US_02_SL.txt and is 5,065 bytes in size.

FIELD OF THE INVENTION

The disclosed present disclosures relate generally to methods foranalyzing nucleic acids.

BACKGROUND OF THE INVENTION

Next-generation sequencing has greatly increased the throughput ofsequencing methods and resulted in new applications for sequencing withimportant real-world implications, such as improvements in cancerdiagnostics and non-invasive prenatal testing for disorders such asDown's Syndrome. There are various technologies for performingnext-generation sequencing, each of which is associated with specifictypes of errors. In addition, these methods share general sources forerrors, such as errors that occur during sample preparation.

Sample preparation for next-generation sequencing typically involvesnumerous amplification steps, each of which generates errors.Amplification reactions, such as PCR, used in sample preparation forhigh-throughput sequencing can include amplifying the initial nucleicacid in the sample to generate the library to be sequenced, clonallyamplifying the library, typically onto a solid support, and additionalamplification reactions to add additional information or functionalitysuch as sample identifying barcodes. Errors can be introduced during anyof the amplification reactions, for example through the misincorporationof bases by a polymerase used for the amplification. It can be difficultto distinguish these errors introduced during sample prep and errorsthat occur during a sequencing reaction, from real and informative SNPs,or mutations present in the initial sample, especially when the SNPs ormutations are present at a low frequency. In addition, calling the baseat each nucleotide can introduce errors as well, usually caused by a lowsignal intensity and/or the surrounding nucleic acid sequence.

There are several known methods to identify errors caused by samplepreparation. One method is to have greater sequencing depth such thatthe sample nucleic acid segment is read multiple times from the samemolecule, or from different copies of the same nucleic acid molecule.These multiple reads can be aligned and a consensus sequence can begenerated. However, SNPs or mutations with low frequency in thepopulation of nucleic acid molecules will appear similar to errorsintroduced during amplification or base calling. Another method toidentify these errors involves tagging nucleic acid molecules such thateach nucleic acid molecule incorporates a unique identifier before beingsequenced. The sequencing results from identically tagged nucleic acidmolecules are pooled and the consensus sequence from these pooledresults is more likely to be the true sequence of the nucleic acid fromthe sample. Amplification errors can be identified if some of theidentically tagged nucleic acid molecules have a different sequence.

Despite these prior methods, there is a need to discover advantageouscombinations of parameters for methods of tagging nucleic acid moleculesthat are highly effective and readily manufacturable, especially foranalyzing complex samples, including mammalian cDNA or genomic samplessuch as, for example, circulating DNA samples. Many prior art methodsrequire the generation of large numbers of unique identifiers and mayalso result in the need for longer unique identifiers. The reactionmixtures in such methods are designed so there is a large excess ofunique identifiers relative to sample nucleic acid molecules. Inaddition to the high cost of making such libraries of uniqueidentifiers, increasing the lengths of the unique identifiers reducesthe amount of sample nucleic acid sequence that can be read in thealready limited read lengths of most next-generation sequencers. Inother prior art disclosures, which sometimes are only prophetic,detailed combinations of parameters are absent, for combinations such asthe diversity of identifiers or the diversity of combinations of any twoidentifiers versus the number of copies of the region of interest, thediversity of identifiers versus the total number of sample nucleic acidmolecules, and the total number of identifiers versus the total numberof sample nucleic acid molecules. This is especially true for samplesthat are complex and isolated from nature, such as cDNA or genomicsamples, including fragmented genomic samples, such as circulating freeDNA in mammalian blood.

There remains a need for a low-cost tagging method, and foridentification of combinations of key parameters for tagging complexsamples isolated from nature. Such a method would provide benefit, forexample, for detecting amplification and base calling errors when usedin a high-throughput sequencing workflow, especially in the analysis ofcomplex, clinically-relevant samples.

SUMMARY OF THE INVENTION

The present disclosure provides improved methods and compositions to tagnucleic acid molecules utilizing Molecular Index Tags (“MITs”) toidentify amplification products arising from individual sample nucleicacids after amplification of a population of sample nucleic acidsmolecules. Furthermore, provided herein are methods that use the MITsfor determining the sequence of sample nucleic acid molecules,identifying errors incurred during sample preparation or base calling,and determining the number of copies of chromosomes or chromosomesegments. Additionally, provided herein are compositions that includereaction mixtures of sample nucleic acid molecules and MITs, populationsof tagged nucleic acid molecules, libraries of MITs, and kits forgenerating tagged nucleic acid molecules using MITs. Accordingly, thepresent disclosure provides methods and compositions for differentiatingerrors that are introduced during sample preparation and base calling,especially during a high-throughput sequencing workflow, from realdifferences that are present in nucleic acid molecules in a startingsample.

Accordingly, provided herein in one aspect is a method for sequencing apopulation of sample nucleic acid molecules, that includes thefollowing: forming a reaction mixture comprising the population ofsample nucleic acid molecules and a set of Molecular Index Tags (MITs),wherein the MITs are nucleic acid molecules, wherein the number ofdifferent MITs in the set of MITs is between 10 and 1,000, and wherein aratio of the total number of sample nucleic acid molecules in thepopulation of sample nucleic acid molecules to the diversity of MITs inthe set of MITs or the diversity of any two MITs in the set of MITs isat least 500:1, 1,000:1, 10,000:1, or 100,000:1; attaching at least oneMIT from the set of MITs to a sample nucleic acid segment of at least50% of the sample nucleic acid molecules to form a population of taggednucleic acid molecules, wherein the at least one MIT is located 5′and/or 3′ to the sample nucleic acid segment on each tagged nucleic acidmolecule and wherein the population of tagged nucleic acid moleculescomprise at least one copy of each MIT of the set of MITs; amplifyingthe population of tagged nucleic acid molecules to create a library oftagged nucleic acid molecules; and determining the sequences of theattached MITs and at least a portion of the sample nucleic acid segmentsof the tagged nucleic acid molecules in the library of tagged nucleicacid molecules, thereby sequencing the population of sample nucleic acidmolecules. The total number of MIT molecules in the reaction mixture istypically greater than the total number of sample nucleic acid moleculesin the reaction mixture.

In some embodiments, the method can include identifying the individualsample nucleic acid molecules that gave rise to the tagged nucleic acidmolecules using the sequences of the at least one MIT on each taggednucleic acid molecule. In some embodiments, the method can furtherinclude before identifying the individual sample nucleic acid molecules,mapping the determined sequence of at least one of the sample nucleicacid segments to a location in the genome of the source from which thesample is derived and using the mapped genome location along with thesequence of the at least one MIT to identify the individual samplenucleic acid molecule that gave rise to the tagged nucleic acidmolecule. Furthermore, in such embodiments a mutation in a nucleic acidsegment or an allele of the nucleic acid segment can be identified.

In some embodiments, the sample can be a mammalian sample, such as ahuman sample, and the sample, for example, can be a blood sample. Thediversity of the combination of any 2 MITs in the set of MITs can exceedthe total number of sample nucleic acid molecules that span each targetlocus of a plurality of target loci of a genome of a mammal that is thesource of the mammalian sample.

In some embodiments, the MITs can be attached during a ligationreaction. In some embodiments, the tagged nucleic acid molecules can beenriched using hybrid capture. In some embodiments, the enriched taggednucleic acid molecules can be clonally amplified onto a solid support ora plurality of solid supports before the sequence is determined usinghigh-throughput sequencing.

In some embodiments, the method can include using a sample where atleast some of the sample nucleic acids comprise at least one target lociof a plurality of target loci from a chromosome or chromosome segment ofinterest. In some embodiments, the method can further include using theidentified sample nucleic acid molecules to measure a quantity of DNAfor each target locus by counting the number of sample nucleic acidmolecules that comprise each target locus; and determining, on acomputer, the number of copies of the one or more chromosomes orchromosome segments of interest using the quantity of DNA at each targetlocus in the sample nucleic acid molecules.

In some embodiments, the sample can include circulating cell-free humanDNA, including circulating tumor DNA, wherein the diversity ofcombinations of any 2 MITs in the set of MITs exceeds the total numberof circulating cell-free DNA fragments or sample nucleic acid moleculesthat span a target locus in the human genome.

Provided herein in another aspect is a method for identifyingamplification errors from sample preparation for high-throughputsequencing or identifying base-calling errors in a high-throughputsequencing reaction of a population of tagged nucleic acid moleculesderived from a sample, that includes the following: forming a reactionmixture comprising the population of sample nucleic acid molecules and aset of Molecular Index Tags (MITs), wherein the MITs are double-strandednucleic acid molecules, wherein the number of different MITs in the setof MITs is between 10 and 100, 250, 500, 1,000, 2,000, 2,500, or 5,000,and wherein a ratio of the total number of sample nucleic acid moleculesin the population of sample nucleic acid molecules to the diversity ofMITs in the set of MITs is greater than 500:1, 1,000:1, 10,000:1, or100,000:1; attaching at least one MIT from the set of MITs to a samplenucleic acid segment of at least one sample nucleic acid molecule of thepopulation of sample nucleic acid molecules to form a population oftagged nucleic acid molecules wherein the at least one MIT is located 5′and/or 3′ to a sample nucleic acid segment on each tagged nucleic acidmolecule and wherein the population of tagged nucleic acid moleculescomprise at least one copy of each MIT in the set of MITs; amplifyingthe population of tagged nucleic acid molecules to create a library oftagged nucleic acid molecules; determining, using high-throughputsequencing, the sequences of the attached MITs and at least a portion ofthe sample nucleic acid segments of the tagged nucleic acid molecules inthe library of tagged nucleic acid molecules, wherein the sequence ofthe at least one MIT on each tagged nucleic acid molecule identifies theindividual sample nucleic acid molecule that gave rise the taggednucleic acid molecule; and identifying tagged nucleic acid moleculeshaving amplification errors by identifying nucleic acid segments thathave a nucleotide sequences that is found in less than 25% of taggednucleic acid molecules derived from the same initial sample nucleic acidmolecule. The total number of MIT molecules in the reaction mixture istypically greater than the total number of sample nucleic acid moleculesin the reaction mixture.

In some embodiments, the method can further include a sample withfragments of genomic DNA that are greater than 20 nucleotides and notmore than 1,000 nucleotides, or greater than 50 nucleotides and not morethan 500 nucleotides in length, and wherein the diversity ofcombinations of any 2 MITs in the set of MITs exceeds the total numberof DNA fragments or sample nucleic acid molecules that span a targetlocus in the genome. In some embodiments, the method can be used forexample, on a maternal blood sample, wherein the copy numberdetermination is for non-invasive prenatal testing. In some embodiments,the method can be used on a blood sample from an individual having orsuspected of having cancer.

In another aspect provided herein is a method of determining the numberof copies of one or more chromosomes or chromosome segments of interestfrom a target individual in a sample of blood or a fraction thereof,from the target individual or from the mother of the target individual,that includes the following: forming a population of tagged nucleic acidmolecules by reacting a population of nucleic acid molecules of thesample with a set of nucleic acid molecular index tags (MITs), whereinthe number of different MITs in the set of MITs is between 10 and 10,000or between 10 and 1,000, wherein a ratio of the total number of samplenucleic acid molecules in the population of sample nucleic acidmolecules to the diversity of MITs in the set of MITs is greater than500:1, 1,000:1, 10,000:1, or 100,000:1, wherein at least some of thesample nucleic acid molecules comprise one or more target loci of aplurality of target loci on the chromosome or chromosome segment ofinterest, and wherein the sample is 1.0 ml or less of blood or afraction of blood derived from 1.0 ml or less of blood; amplifying thepopulation of enriched tagged nucleic acid molecules to create a libraryof tagged nucleic acid molecules; determining the sequences of theattached MITs and at least a portion of the sample nucleic acid segmentsof the tagged nucleic acid molecules in the library of tagged nucleicacid molecules, to determine the identity of a sample nucleic acidmolecule that gave rise to a tagged nucleic acid molecule; measuring aquantity of DNA for each target locus by counting the number of samplenucleic acid molecules that comprise each target locus using thedetermined identities; and determining, on a computer, the number ofcopies of the one or more chromosomes or chromosome segments of interestusing the quantity of DNA at each target locus in the sample nucleicacid molecules. The total number of MIT molecules in the reactionmixture is typically greater than the total number of sample nucleicacid molecules in the reaction mixture.

In some embodiments, the number of target loci and the volume of thesample provide an effective amount of total target loci to achieve adesired sensitivity and specificity for the copy number determination.In some embodiments, the method can further include using a number oftarget loci and a total number of sample nucleic acid molecules thatspan the target loci to provide an effective amount of total sequencingreads to achieve a desired sensitivity and specificity for the copynumber determination. In some embodiments, this can be at least 10, 25,50, 100, 250, 500, 1,000, 1,500, 2,000, 2,500, 3,000, 4,000, 5,000,6,000, 7,000, 8,000, 9,000, 10,000, 15,000, 20,000, 25,000, 30,000,40,000, or 50,000 target loci. In some embodiments, the method caninclude at least 10,000, 100,000, 500,000, or 1,000,000 total targetloci in the sample, wherein the set of MITs comprises at least 25, 30,32, 50, 64, 100, 200, 250, 500, or 1,000 MITs, wherein the sample isfrom the mother and includes at least 1%, 2%, 3%, 4%, or 5% fetalnucleic acids compared to maternal nucleic acids, and wherein thedesired specificity is 95%, 96%, 97%, 98%, or 99% and the desiredsensitivity is 95%, 96%, 97%, 98%, or 99%.

In some embodiments, the method can include a ligation reaction to formthe population of tagged nucleic acid molecules, wherein the populationof tagged nucleic acid molecules are enriched using hybrid capturebefore amplifying, and wherein the number of total target loci in thesample is at least 4, 5, 6, 7, 8, 9, 10, 15, or 20 times greater thanthe number of total target loci required to meet the desired specificityand the desired sensitivity.

In some embodiments, the method can further include determining aprobability of each copy number hypothesis from a set of copy numberhypotheses for the one or more chromosomes or chromosome segments ofinterest using the quantity of DNA at each target locus and selectingthe copy number hypothesis with the highest probability.

In some embodiments, the method can include using a plurality of disomicloci from one or more chromosome or chromosome segments expected to bedisomic on the sample nucleic acid molecules to determine theprobability of each copy number hypothesis by comparing the quantity ofDNA at the plurality of target loci to the quantity of DNA at thedisomic loci.

In some embodiments, the method can be used on a maternal blood samplewherein the copy number determination is for non-invasive prenataltesting. In some embodiments, the method can be used on a blood samplefrom an individual having or suspected of having cancer.

Another aspect provided herein is a reaction mixture that includes: apopulation of at least 100,000, 200,000, 250,000, 500,000,000, or1,000,000 sample nucleic acid molecules between 10, 20, 25, 50, or 100and 200, 250, 500, 1,000, 2,000, or 2,500 nucleotides in length; a setof between 10 and 100, 200, 250, 500, 1,000, or 10,000 Molecular IndexTags (MITs) between 3, 4, 5, 6, or 7 nucleotides in length on the lowend of the range and 8, 9, 10, 11, 12, 15, or 20 nucleotides in lengthon the high end of the range; and a ligase, wherein the MITs areseparate nucleic acid molecules from the sample nucleic acid molecules,wherein the total number of MIT molecules in the reaction mixture isgreater than the total number of sample nucleic acid molecules in thereaction mixture, wherein a ratio of the total number of sample nucleicacid molecules in the reaction mixture to the diversity of the MITs inthe set of MITs in the reaction mixture is at least 1,000:1, 10,000:1,or 100,000:1, wherein the sequence of each of the MITs in the set ofMITs differs from all other MIT sequences in the set by at least 2nucleotides; and wherein the reaction mixture comprises at least twocopies of every MIT.

In another aspect, the present disclosure provides a method ofdetermining the number of copies of one or more chromosomes orchromosome segments of interest in a sample of blood or a fractionthereof, from a target individual, the method including: forming areaction mixture comprising a population of sample nucleic acidmolecules derived from the sample and a set of at least 32 MolecularIndex Tags (MITs), wherein each MIT in the set of MITs is adouble-stranded nucleic acid molecule comprising a different nucleicacid sequence, wherein the sample is derived from no more than 1.0 ml ofblood, wherein a ratio of the total number of sample nucleic acidmolecules in the population of sample nucleic acid molecules to thediversity of MITs in the set of MITs is greater than 1,000:1, andwherein at least some of the sample nucleic acid molecules comprise oneor more target loci of at least 1,000 target loci on the chromosome orchromosome segment of interest; attaching at least two MITs from the setof MITs to a sample nucleic acid segment of at each sample nucleic acidmolecule of the population of sample nucleic acid molecules to form apopulation of tagged nucleic acid molecules wherein each of the at leasttwo MITs is located 5′ and/or 3′ to a sample nucleic acid segment oneach tagged nucleic acid molecule and wherein the population of taggednucleic acid molecules comprise at least one copy of each MIT of the setof MITs; amplifying the population of tagged nucleic acid molecules tocreate a library of tagged nucleic acid molecules; determining thesequences of the attached MITs and at least a portion of the samplenucleic acid segments of the tagged nucleic acid molecules in thelibrary of tagged nucleic acid molecules, wherein the sequence of theattached MITs and the at least a portion of the nucleic segment on eachtagged nucleic acid molecule are used to identify tagged nucleic acidmolecules that belong to the same paired MIT nucleic acid segmentfamily, wherein the at least two MITs on each member of a paired MITnucleic acid segment family are identical or complementary, whereinnucleic acid molecule segments of each member of an MIT nucleic acidsegment family map to the same coordinates on the genome of the sourceof the population of sample nucleic acid molecules, and wherein at least25% of the sample nucleic acid molecules are represented in the libraryof tagged nucleic acid molecules whose sequence is determined;determining for the sample nucleic acid molecules, a quantity of DNA foreach target locus by counting the number of MIT nucleic acid segmentfamilies that span each target locus; and determining, on a computer,the number of copies of the one or more chromosomes or chromosomesegments of interest using the quantity of DNA at each target locus inthe sample nucleic acid molecules. The total number of MIT molecules inthe reaction mixture is typically greater than the total number ofsample nucleic acid molecules in the reaction mixture. MIT nucleic acidsegment families share identical MITs in the same relative positions tothe nucleic acid segment as well as the same fragment end positions andthe same sequenced orientation (positive or negative relative to thehuman genome). Each sample nucleic acid molecule that entered into theMIT library preparation process can generate two families, one mappingto each of the positive and negative genomic orientations. Two MITnucleic acid segment families can be paired, one with a positiveorientation and one with a negative orientation, if the MIT nucleic acidsegment families contain complementary MITs in the same relativeposition to the same nucleic acid segment as well as complementaryfragment end positions. In some embodiments, the paired MIT nucleic acidsegment families can be used to verify the presence of sequencedifferences in the sample nucleic acid molecule.

In some embodiments, the method can further include analyzingsingle-nucleotide polymorphic loci for the one or more target loci onthe one or more chromosomes or chromosome segments. In furtherembodiments, before determining the number of copies of the one or morechromosomes or chromosome segments of interest, a ratio of samplenucleic acid molecules comprising different alleles at each locus can beestimated by counting the number of MIT nucleic acid segment familiesthat include each allele at each locus and using the estimated ratio ofsample nucleic acid molecules including different alleles at each locusto determine the number of copies of the one or more chromosomes orchromosome segments of interest.

In some embodiments, the method can include a sample of circulatingcell-free human DNA wherein the diversity of possible combinations ofany 2 MITs in the set of MITs exceeds the number of circulatingcell-free DNA fragments or sample nucleic acid molecules in the reactionmixture that span one or more target loci in the human genome.

In some embodiments, the method can include analyzing a plurality ofdisomic loci on a chromosome or chromosome segment expected to bedisomic, wherein the method further includes determining for the samplenucleic acid molecules, a quantity of DNA for each disomic locus bycounting the number of MIT nucleic acid segment families that span eachdisomic locus, and wherein the determining the number of copies of theone or more chromosomes or chromosome segments of interest uses thequantity of DNA for each target locus and the quantity of DNA for eachdisomic locus.

In some embodiments, the method can further include creating, on acomputer, a plurality of ploidy hypotheses each pertaining to adifferent possible ploidy state of the chromosome or chromosome segmentof interest and determining, on a computer, a relative probability ofeach of the ploidy hypotheses using the quantity of DNA for each targetlocus to identify the copy number of the individual by selecting theploidy state corresponding to the hypothesis with the greatestprobability.

In some embodiments, the method can be used on a maternal sample whereinthe copy number determination is for non-invasive prenatal testing. Insome embodiments, the method can be used on a sample from an individualhaving or suspected of having cancer.

In another aspect, provided herein is a method of determining the numberof copies of one or more chromosomes or chromosome segments of interestin a sample of blood or a fraction thereof, from a target individual,where the method includes: forming a population of tagged nucleic acidmolecules by reacting a population of sample nucleic acid molecules anda set of Molecular Index Tags (MITs), wherein the sample is 2.5, 2.0,1.0, or 0.5 ml or less, wherein the number of different MITs in the setof MITs is between 10 and 100, 200, 250, 500, 1,000, 2,000, 2,500,5,000, or 10,000, wherein a ratio of the total number of sample nucleicacid molecules in the population of sample nucleic acid molecules to thediversity of MITs in the set of MITs is at least 100:1, 500:1, 1,000:1,10,000:1, or 100,000:1, wherein each tagged nucleic acid moleculecomprises one or two MITs located 5′ and 3′, respectively, for exampletwo MITs located 5′ and 3′, respectively, to a nucleic acid segment fromthe population of nucleic acid molecules, and wherein a portion of thesample nucleic acid molecules comprise one or more target loci of aplurality of loci on the chromosome or chromosome segment of interest;amplifying the population of tagged nucleic acid molecules to create alibrary of tagged nucleic acid molecules; and determining the sequencesof the attached MITs and at least a portion of the sample nucleic acidsegments of the tagged nucleic acid molecules in the library of taggednucleic acid molecules, for example determining the sequence of at least10, 20, 30, 40, 50, 60, 70, 80, 90, or 95%, or 100% of the samplenucleic acid segments, wherein the sequence of the attached MITs and theat least a portion of the nucleic segment on each tagged nucleic acidmolecule are used to identify tagged nucleic acid molecules that belongto the same paired MIT nucleic acid segment family, wherein the at leasttwo MITs on each member of a paired MIT nucleic acid segment family areidentical or complementary, and wherein nucleic acid molecule segmentsof each member of an MIT nucleic acid segment family map to the samecoordinates on the genome of the source of the population of samplenucleic acid molecules; determining for the sample nucleic acidmolecules, a quantity of DNA for each target locus by counting thenumber of MIT nucleic acid segment families that span each target locus;and determining, on a computer, the number of copies of the one or morechromosomes or chromosome segments of interest using the quantity of DNAat each target locus in the sample nucleic acid molecules. The totalnumber of MIT molecules in the reaction mixture is typically greaterthan the total number of sample nucleic acid molecules in the reactionmixture.

In some embodiments, the method can further include creating, on acomputer, a plurality of ploidy hypotheses each pertaining to adifferent possible ploidy state of the chromosome or chromosome segmentof interest and determining, on a computer, a relative probability ofeach of the ploidy hypotheses using the quantity of DNA for each targetlocus to identify the copy number of the individual by selecting theploidy state corresponding to the hypothesis with the greatestprobability.

In some embodiments, the method can be used on a maternal blood samplewherein the copy number determination is for non-invasive prenataltesting. In some embodiments, the method can be used on a blood samplefrom an individual having or suspected of having cancer.

In another aspect, provided herein is a reaction mixture which includes:a population of between 500,000,000 and 1,000,000,000,000 sample nucleicacid molecules between 10 and 1,000 nucleotides in length; a set ofbetween 10 and 1,000 Molecular Index Tags (MITs) between 4 and 8nucleotides in length; and a ligase, wherein the MITs are nucleic acidmolecules, wherein a ratio of the total number of the sample nucleicacid molecules in the reaction mixture to the diversity of the MITs inthe set of MITs is between 1,000:1 and 1,000,000:1, wherein the sequenceof each of the MITs in the set of MITs differs from all other MITsequences in the set by at least 2 nucleotides, and wherein the setcomprises at least two copies of every MIT.

In some embodiments, the method can further include using sample nucleicacid molecules that have not been amplified in vitro. In someembodiments, the method can be used on a maternal sample wherein thecopy number determination is for non-invasive prenatal testing. In someembodiments, the method can be used on a sample from an individualhaving or suspected of having cancer.

In another aspect, provided herein is a reaction mixture that includes:a population of between 500,000,000 and 5,000,000,000,000 sample nucleicacid molecules; and a set of primers with sequences designed to bind tointernal sequences of the sample nucleic acid molecules; wherein theprimers further comprise a Molecular Index Tag (MIT) from a set ofbetween 10 and 500 MITs, wherein the MITs are nucleic acid moleculesbetween 4 and 8 nucleotides in length, wherein a ratio of the diversityof the sample nucleic acid molecules in the reaction mixture to thediversity of the MITs in the set of MITs in the reaction mixture isbetween 10,000:1 and 1,000,000:1, and wherein the sequence of each ofthe MITs in the set of MITs differs from all other MIT sequences in theset by at least 2 nucleotides.

In some embodiments, the method can further include having more primersin the reaction mixture than the total number of sample nucleic acidmolecules.

In another aspect, provided herein is a population of tagged nucleicacid molecules that includes: between 500,000,000 and 5,000,000,000,000different tagged nucleic acid molecules between 10 and 1,000 nucleotidesin length, wherein each of the tagged nucleic acid molecules comprise atleast one Molecular Index Tag (MIT) located 5′ and/or 3′ to a samplenucleic acid segment, wherein the at least one MIT is a member of a setof between 10 and 500 different MITs each between 4 and 20 nucleotidesin length, wherein the population of tagged nucleic acid moleculescomprises each member of the set of MITs, wherein at least two taggednucleic acid molecules of the population comprise at least one identicalMIT and a sample nucleic acid segment that is greater than 50%different, and wherein a ratio of the number of sample nucleic acidsegments to the number of MITs in the population is between 1,000:1 and1,000,000,000:1.

In some embodiments, the population of tagged nucleic acid molecules canbe a part of a reaction mixture that further includes a polymerase or aligase. In various embodiments, the population of nucleic acid moleculescan be used to generate a library, wherein the library includes between1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 25, 50, 100, 250, 500, and 1,000 copiesof some or all of the population of nucleic acid molecules on the lowend of the range and 3, 4, 5, 6, 7, 8, 9, 10, 25, 50, 100, 250, 500,1,000, 2,500, 5,000, and 10,000 copies of some or all of the populationof nucleic acid molecules on the high end of the range. In someembodiments, the library can include at least 2, 3, 4, 5, 6, 7, 8, 9,10, 15, 20, 25, 50, 100, 250, 500, or 1,000 tagged nucleic acidmolecules with MITs with identical sequences and a sample nucleic acidsegment that is between 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 96%,97%, 98%, 99%, and 99.9% identical on the low end of the range and 60%,70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, 99.9%, and 100%identical on the high end of the range. In various embodiments, thelibrary can include at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 50,100, 250, 500, or 1,000 tagged nucleic acid molecules with MITs withidentical sequences and a sample nucleic acid segment that has at least1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, or 25 nucleotidedifferences. In some embodiments, the library of nucleic acid moleculescan be clonally amplified onto a solid support or a plurality of solidsupports.

In another aspect, provided herein is a population of tagged nucleicacid molecules, wherein the population is formed by a method including:attaching at least one Molecular Index Tag (MIT) to a population ofbetween 500,000,000 and 5,000,000,000,000 sample nucleic acid moleculescomprising sample nucleic acid segments between 50 and 500 nucleotidesin length, to form a tagged nucleic acid molecule comprising at leastone MIT located 5′ and/or 3′ to a sample nucleic acid segment whereinthe MITs are nucleic acid molecules, wherein the MITs are members of aset of between 10 and 500 different MITs each between 4 and 20nucleotides in length, wherein the population of tagged nucleic acidmolecules comprises each member of the set of MITs, wherein at least twotagged nucleic acid molecules of the population comprise at least oneidentical MIT and a sample nucleic acid segment that is greater than 50%different, and wherein a ratio of the diversity of sample nucleic acidmolecule segments in the population to the diversity of MITs in the setof MITs is between 1,000:1 and 1,000,000,000:1.

In another aspect, provided herein is a kit including: a first containercomprising a ligase; and a second container comprising a set ofMolecular Index Tags (MITs), wherein each MIT in the set of MITscomprises a portion of a Y-adapter nucleic acid molecule of a set ofY-adapter nucleic acid molecules, where each Y-adapter of the setcomprises a base-paired, double-stranded polynucleotide segment and atleast one non-base-paired single-stranded polynucleotide segment,wherein the sequence of each of the Y-adapter nucleic acid molecules inthe set, other than the MIT sequence, is identical, and wherein the MITis a double-stranded sequence that is part of the base-paired,double-stranded polynucleotide segment, wherein the set of MITscomprises between 10 and 500 MITs, wherein the MITs are between 4 and 8nucleotides in length, and wherein the sequence of each of the MITs inthe set of MITs differs from all other MIT sequences in the set by atleast 2 nucleotides. The kit can further include a polymerase.

In some embodiments disclosed herein, the present disclosure provides areaction mixture wherein a population of sample nucleic acid moleculesis combined with a set of MITs under appropriate conditions to attachthe MITs to the nucleic acid molecules or to a nucleic acid segment ofthe nucleic acid molecule to generate a population of tagged nucleicacid molecules. In some embodiments disclosed herein, the population oftagged nucleic acid molecules can be processed, for example byamplification(s), which can be part of a high-throughput sequencingsample preparation workflow, and used for downstream analysis, such asby high-throughput sequencing. The MITs can be attached through directligation or as a portion of an amplification, such as a PCR primer.Typically, MITs are 5′ to the sequence-specific binding region of theprimer but the primers can be designed such that they are between auniversal binding region and a sequence-specific binding region, or theMITs are internal to the sequence-specific binding region and form aloop upon hybridization with a sample nucleic acid molecule. In someembodiments, the MITs can be on forward primers such that amplificationwith the primers generates tagged nucleic acid molecules with MITs 5′ tothe target locus. In some embodiments, the MITs can be on reverseprimers such that amplification with the primers generates taggednucleic acid molecules with MITs 3′ to the target locus. In someembodiments, the MITs can be on both forward and reverse primers suchthat amplification with the primers generates tagged nucleic acidmolecules with MITs both 5′ and 3′ to the target locus.

In some embodiments disclosed herein, the MITs can be single-stranded ordouble-stranded nucleic acid molecules. In some embodiments, thesequences of the MIT can differ from the sequences of all the other MITsin the set of MITs by at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10nucleotides. In some embodiments, the MITs in the set of MITs aretypically the same length. In other embodiments, the MITs in the set ofMITs are different length. In any of the embodiments disclosed herein,the lengths of the MITs are 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30nucleotides in length.

In some embodiments, the MITs can be at least a portion of a Y-adaptoror a single-stranded oligonucleotide or double-stranded nucleic acid,such as a double-stranded adaptor. In some embodiments, the MITs can bea portion of a Y-adapter nucleic acid molecule of a set of Y-adapternucleic acid molecules, where each Y-adapter of the set includes abase-paired, double-stranded polynucleotide segment and at least onenon-base-paired single-stranded polynucleotide segment, wherein thesequence of each of the Y-adapter nucleic acid molecules in the set,other than the MIT sequence, is identical, and wherein the MIT is adouble-stranded sequence that is part of the base-paired,double-stranded polynucleotide segment. In some embodiments, thedouble-stranded polynucleotide segment can be between 5, 10, 15, and 20nucleotides in length on the low end of the range and 10, 15, 20, 25,30, 35, 40, 45, and 50 nucleotides in length on the high end of therange, not including the MIT, and the single-stranded polynucleotidesegment can be between 5, 10, 15, and 20 nucleotides in length on thelow end of the range and 10, 15, 20, 25, 30, 35, 40, 45, and 50nucleotides in length on the high end of the range. In some embodiments,the MITs can be between 3, 4, 5, 6, 7, 8, 9, 10, or 15 nucleotides inlength on the low end of the range and 5, 6, 7, 8, 9, 10, 15, 20, 25, or30 nucleotides in length on the high end of the range. In someembodiments disclosed herein, the MITs can be portions ofoligonucleotides that further include sequences designed to bind to thesample nucleic acid molecules, universal primer binding sequences,and/or adapter sequences, especially adapter sequences useful forhigh-throughput sequencing. In some embodiments, the total lengths ofthe oligonucleotides can be between 10, 15, 20, 25, 30, 35, 40, 45, 50,60, 70, 80, 90, or 100 nucleotides on the low end of the range and 25,30, 35, 40, 45, 50, 60, 70, 80, 90, or 100 nucleotides on the high endof the range. In some embodiments, one or more MITs can be attached tothe sample nucleic acid molecules. For example, in some embodiments, atleast 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 MITs can be attached to thesample nucleic acid molecules. In some embodiments disclosed herein, theMITs can be attached 5′ and/or 3′ to the sample nucleic acid segment,which can be a portion or all of a sample nucleic acid molecule. In someembodiments, 2 MITs can be attached to the individual sample nucleicacid molecules, for example each of the sample nucleic acid molecules,wherein each tagged nucleic acid molecule comprises two MITs located 5′and 3′ respectively, to a nucleic acid segment from the population ofnucleic acid molecules.

In some embodiments disclosed herein, the sample nucleic acid moleculescan be used in the reaction mixture before any other in vitroamplification has occurred. In some embodiments, the total number ofsample nucleic acid molecules in the population of nucleic acidmolecules can be between 100, 250, 500,1,000, 2,500, 5,000,10,000,25,000, 50,000,100,000, 250,000, 500,000, 1×10⁶, 2.5×10⁶, 5×10⁶, 1×10⁷,1×10⁸, 1×10⁹, and 1×10¹⁰ sample nucleic acid molecules on the low end ofthe range and 500, 1,000, 2,500, 5,000, 10,000, 25,000, 50,000, 100,000,250,000, 500,000, 1×10⁶, 2.5×10⁶, 5×10⁶, 1×10⁷, 1×10⁸, 1×10⁹, 1×10¹⁰,1×10¹¹, and 1×10¹² sample nucleic acid molecules on the high end of therange. In some embodiments disclosed herein, the total number of samplenucleic acid molecules in the reaction mixture can be greater than thediversity of the MITs in the set of MITs. For example, a ratio of thetotal number of sample nucleic acid molecules to the diversity of theMITs in the set of MITs can be at least 2:1, 10:1, 100:1, 1,000:1,5,000:1, 10,000:1, 25,000:1, 50,000:1, 100,000:1, 250,000:1, 500,000:1,1,000,000:1, 5,000,000:1, 10,000,000:1, 1×10⁸:1 1×10⁹:1, 1×10¹⁰:1, ormore. In some embodiments, the diversity of the possible combinations ofattached MITs can be greater than the total number of sample nucleicacid molecules in the reaction mixture that span a target locus. Forexample, a ratio of the diversity of the possible combinations ofattached MITs, for example combinations of any 2, 3, 4, 5, etc. MITsdepending on how many MITs are attached to the sample nucleic acidmolecules, to the total number of sample nucleic acid molecules thatspan a target locus can be at least 1:01, 1.1:1, 1.5:1, 2:1, 3:1, 4:1,5:1, 6:1, 7:1 8:1, 9:1, 10:1, 15:1, 20:1, 25:1, 50:1, 100:1, 500:1 or,1,000:1. In some embodiments, the MITs in the set of MITS can beattached to at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 25, 50, 100, 250,500,1,000, 2,500, 5,000,10,000, 25,000, 50,000,100,000, 250,000,500,000, 1×10⁶, 2.5×10⁶, 5×10⁶, 1×10⁷, 1×10⁸, 1×10⁹, 1×10¹⁰, 1×10¹¹, or1×10¹² different sample nucleic acid molecules to form the population oftagged nucleic acid molecules.

In some embodiments disclosed herein, at least 1, 2, 3, 4, 5, 6, 7, 8,9, 10, 25, 50, 100, 250, 500, 1,000, 2,500, 5,000, 10,000, 25,000,50,000, 100,000, 250,000, 500,000, 1×10⁶, 2.5×10⁶, 5×10⁶, 1×10⁷, 1×10⁸,1×10⁹, 1×10¹⁰, 1×10¹¹, and 1×10¹² sample nucleic acid molecules can haveMITs attached in the reaction mixture. In some embodiments, at least 1%,2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%,70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, 99.9%, or 100% of thesample nucleic acid molecules in the reaction mixture can have MITsattached.

In some embodiments disclosed herein, the reaction mixture can includemore MIT molecules than sample nucleic acid molecules. For example, insome embodiments, the total number of MIT molecules in the reactionmixture can be least 2, 3, 4, 5, 6, 7, 8, 9, or 10 times greater thanthe total number of sample nucleic acid molecules in the reactionmixture. In certain respects, the fold difference is dependent on thenumber of MITs to be attached. For example, if 2 MITs are to beattached, then the total number of MIT molecules in the reaction mixturecan be least 2 times greater than to the total number of sample nucleicacid molecules in the reaction mixture; if 3 MITs are to be attached,then the total number of MIT molecules in the reaction mixture can beleast 3 times greater than to the total number of sample nucleic acidmolecules in the reaction mixture, and so on. In some embodiments, theratio of the total number of MITs with identical sequences in thereaction mixture to the total number of nucleic acid molecules in thereaction mixture can be between 0.1:1, 0.2:1, 0.3:1, 0.4:1, 0.5:1, 1:1,1.5:1 and 2:1 on the low end of the range and 0.3:1, 0.4:1, 0.5:1, 1:1,1.5:1, 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, 9:1, and 10:1 on the high endof the range.

In some embodiments, the sequences of the attached MITs and nucleic acidsegments in the population of tagged nucleic acid molecules can bedetermined through sequencing, especially high-throughput sequencing. Insome embodiments, the tagged nucleic acid molecules can be clonallyamplified in preparation for sequencing, especially onto a solid supportor a plurality of solid supports. In some embodiments, the determinedsequences of the MITs on a tagged nucleic acid molecule can be used toidentify the sample nucleic acid molecule from which the tagged nucleicacid molecule is derived, especially using the sequences of the ends ofthe nucleic acid segment or fragment-specific insert ends as disclosedherein. In some embodiments, the determined sequence of the nucleic acidsegment on the tagged nucleic acid molecule can be used to aid in theidentification of the sample nucleic acid molecules from which thetagged nucleic acid molecule is derived. In some embodiments, thedetermined sequence of the nucleic acid segment can be mapped to alocation in the genome of the source of the sample nucleic acidmolecules and this information can be used to aid in the identification.

In some embodiments, between 100, 250, 500, 1,000, 2,500, 5,000, 10,000,25,000, 50,000, 100,000, 250,000, 500,000, 1×10⁶, 2.5×10⁶, 5×10⁶, 1×10⁷,1×10⁸, 1×10⁹, and 1×10¹⁰ tagged nucleic acid molecules on the low end ofthe range and 500, 1,000, 2,500, 5,000, 10,000, 25,000, 50,000, 100,000,250,000, 500,000, 1×10⁶, 2.5×10⁶, 5×10⁶, 1×10⁷, 1×10⁸, 1×10⁹, 1×10¹⁰,1×10¹¹, and 1×10¹² tagged nucleic acid molecules on the high end of therange can be identified. In some embodiments, the tagged nucleic acidmolecules derived from the two strands of one sample nucleic acidmolecule can be identified and used to generate paired MIT families. Indownstream sequencing reactions, where single-stranded nucleic acidmolecules are typically sequenced, an MIT family can be identified byidentifying tagged nucleic acid molecules with identical orcomplementary MIT sequences. In these embodiments, the paired MITfamilies can be used to verify the presence of sequence differences inthe sample nucleic acid molecule. In some further embodiments, thedetermined sequences of the nucleic acid segments are used to generatepaired MIT nucleic acid segment families that have complementary oridentical MIT and nucleic acid segment sequences. In these embodiments,the paired MIT nucleic acid segment families can be used to verify thepresence of sequence differences in the sample nucleic acid molecule.

In some embodiments, tagged nucleic acid molecules with particulartarget loci can be enriched. In some embodiments, one-sided or two-sidedPCR can be used to enrich these target loci on one or more chromosomes.In some embodiments, hybrid capture can be used. In some embodiments,between 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 50, 100, 250, 500,1,000, 2,500, 5,000, 10,000, 15,000, or 20,000 target loci on the lowend of the range and 5, 6, 7, 8, 9, 10, 15, 20, 25, 50, 100, 250, 500,1,000, 2,500, 5,000, 10,000, 15,000, 20,000, 25,000, 50,000, 100,000,and 250,000 target loci on the high end of the range can be targeted forenrichment. In some embodiments, the target loci can be between 1, 2, 3,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50,75, and 100 nucleotides in length on the low end of the range and 10,11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75, 100, 125, 150, 200,250, 300, 400, 500, and 1,000 nucleotides in length on the high end ofthe range. In some embodiments, the target loci on different samplenucleic acid molecules can be at least 50%, 60%, 70%, 80%, 90% 95%, 96%,97%, 98%, 99%, 99.9%, or 100% identical or share at least 50%, 60%, 70%,80%, 90% 95%, 96%, 97%, 98%, 99%, 99.9%, or 100% sequence identity.

In some embodiments disclosed herein, the sample can be from a mammal.In some embodiments, the sample can be from a human, especially from ahuman blood sample or a fraction thereof. In any of the disclosedembodiments, the sample can be less than 0.1, 0.2, 0.25, 0.5, 1, 1.25,1.5, 1.75, 2, 2.5, 3, 3.5, 4, 4.5 or 5 ml of blood or plasma. In someembodiments disclosed herein, the sample can include circulatingcell-free human DNA. In some embodiments, the sample includingcirculating cell-free human DNA can be from a mother and can includematernal and fetal DNA. In some embodiments, the sample can includecirculating cell-free human DNA can be a blood sample from a personhaving or suspected of having cancer and can include normal and tumorDNA.

Other features and advantages of the present disclosure will be apparentfrom the following detailed description and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic showing the attachment of two MITs to a nucleicacid molecule or nucleic acid segment using ligation. FIG. 1 disclosesSEQ ID NOS 1-2, 2, 1, 3-4, 4 and 3, respectively, in order ofappearance.

FIG. 2 is a schematic showing the incorporation of two MITs into anucleic acid molecule or nucleic acid segment using PCR with primerscontaining the MIT sequences. FIG. 2 discloses SEQ ID NOS 5-6, 6, 5,7-8, 8, 7 and 9-14, respectively, in order of appearance.

FIGS. 3A-3B illustrate the structures of amplicons produced by differentexemplary methods provided herein. The amplicon generated after 1-sidedSTAR (FIG. 3A) has an MIT on one side wherein the first base of the MITis the first base in Read 1 or Read 2 depending on how 1-sided STAR isperformed. In FIG. 3A, the first base of the MIT would be the first basein Read 2. The amplicon generated after hybrid capture (FIG. 3B) hasMITs on both sides of the amplicon wherein the first base of Read 1 isthe first base of MIT1 and the first base of Read 2 is the first base ofMIT2.

FIG. 4 is a table showing the results of a sequencing run using MITs.

FIG. 5 is a bar graph that shows the average error rate and the averagepaired MIT nucleic acid segment family error rate of two samples inthree different experimental runs (data from FIG. 4).

The above-identified figures are provided by way of representation andnot limitation.

DETAILED DESCRIPTION OF THE INVENTION

The present disclosure relates to methods and compositions that includeoligonucleotide tags, herein referred to as Molecular Index Tags (MITs),that are attached to a population of nucleic acid molecules from asample to identify individual sample nucleic acid molecules from thepopulation of nucleic acid molecules (i.e. members of the population)after sample processing for a sequencing reaction. The sequencingreaction in some embodiments, is a high-throughput sequencing reactionperformed on tagged nucleic acid molecules that are derived from samplenucleic acid molecules. Unlike prior art methods that relate to uniqueidentifiers and teach having a diversity of unique identifiers that isgreater than the number of sample nucleic acid molecules in a sample inorder to tag each sample nucleic acid molecule with a unique identifier,the present disclosure typically involves many more sample nucleic acidmolecules than the diversity of MITs in a set of MITs. In fact, methodsand compositions herein can include more than 1,000, 1×10⁶, 1×10⁹, oreven more starting molecules for each different MIT in a set of MITs.Yet the methods can still identify individual sample nucleic acidmolecules that give rise to a tagged nucleic acid molecule afteramplification.

In the methods and compositions herein, the diversity of the set of MITsis advantageously less than the total number of sample nucleic acidmolecules that span a target locus but the diversity of the possiblecombinations of attached MITs using the set of MITs is greater than thetotal number of sample nucleic acid molecules that span a target locus.Typically, to improve the identifying capability of the set of MITs, atleast two MITs are attached to a sample nucleic acid molecule to form atagged nucleic acid molecule. The sequences of attached MITs determinedfrom sequencing reads can be used to identify clonally amplifiedidentical copies of the same sample nucleic acid molecule that areattached to different solid supports or different regions of a solidsupport during sample preparation for the sequencing reaction. Thesequences of tagged nucleic acid molecules can be compiled, compared,and used to differentiate nucleotide mutations incurred duringamplification from nucleotide differences present in the initial samplenucleic acid molecules.

Sets of MITs in the present disclosure typically have a lower diversitythan the total number of sample nucleic acid molecules, whereas manyprior methods utilized sets of “unique identifiers” where the diversityof the unique identifiers was greater than the total number of samplenucleic acid molecules. Yet MITs of the present disclosure retainsufficient tracking power by including a diversity of possiblecombinations of attached MITs using the set of MITs that is greater thanthe total number of sample nucleic acid molecules that span a targetlocus. This lower diversity for a set of MITs of the present disclosuresignificantly reduces the cost and manufacturing complexity associatedwith generating and/or obtaining sets of tracking tags. Although thetotal number of MIT molecules in a reaction mixture is typically greaterthan the total number of sample nucleic acid molecules, the diversity ofthe set of MITs is far less than the total number of sample nucleic acidmolecules, which substantially lowers the cost and simplifies themanufacturability over prior art methods. Thus, a set of MIT's caninclude a diversity of as few as 3, 4, 5, 10, 25, 50, or 100 differentMITs on the low end of the range and 10, 25, 50, 100, 200, 250, 500, or1000 MITs on the high end of the range, for example. Accordingly, in thepresent disclosure this relatively low diversity of MITs results in afar lower diversity of MITs than the total number of sample nucleic acidmolecules, which in combination with a greater total number of MITs inthe reaction mixture than total sample nucleic acid molecules and ahigher diversity in the possible combinations of any 2 MITs of the setof MITs than the number of sample nucleic acid molecules that span atarget locus, provides a particularly advantageous embodiment that iscost-effective and very effective with complex samples isolated fromnature. Furthermore, by mapping sequenced nucleic acid molecules to thegenome additional advantages are provided such as simpler analytics andidentifying information about the sequence of the sample nucleic acidmolecule compared to the reference genome.

Brief Description of Illustrative Methods

Accordingly, provided herein in one aspect is a method for sequencing apopulation of sample nucleic acid molecules, that can optionally furtherinclude using the sequencing to identify individual sample nucleic acidmolecules from a population of sample nucleic acid molecules. In someembodiments, the population of nucleic acid molecules has not beenamplified in vitro before attaching the MITs and can include between1×10⁸ and 1×10¹³, or in some embodiments, between 1×10⁹ and 1×10¹² orbetween 1×10¹⁰ and 1×10¹², sample nucleic acid molecules. In someembodiments, the methods include forming a reaction mixture thatincludes the population of nucleic acid molecules and a set of MITs,wherein the total number of nucleic acid molecules in the population ofnucleic acid molecules is greater than the diversity of MITs in the setof MITs and wherein there are at least three MITs in the set. In someembodiments, the diversity of the possible combinations of attached MITsusing the set of MITs is more than the total number of sample nucleicacid molecules that span a target locus and less than the total numberof sample nucleic acid molecules in the population. In some embodiments,the diversity of set of MITs can include between 10 and 500 MITs withdifferent sequences. The ratio of the total number of nucleic acidmolecules in the population of nucleic acid molecules in the sample tothe diversity of MITs in the set, in certain methods and compositionsherein, can be between 1,000:1 and 1,000,000,000:1. The ratio of thediversity of the possible combinations of attached MITs using the set ofMITs to the total number of sample nucleic acid molecules that span atarget locus can be between 1.01:1 and 10:1. The MITs typically arecomposed at least in part of an oligonucleotide between 4 and 20nucleotides in length as discussed in more detail herein. The set ofMITs can be designed such that the sequences of all the MITs in the setdiffer from each other by at least 2, 3, 4, or 5 nucleotides.

In some embodiments, provided herein, at least one (e.g. two) MIT fromthe set of MITs are attached to each nucleic acid molecule or to asegment of each nucleic acid molecule of the population of nucleic acidmolecules to form a population of tagged nucleic acid molecules. MITscan be attached to a sample nucleic acid molecule in variousconfigurations, as discussed further herein. For example, afterattachment one MIT can be located on the 5′ terminus of the taggednucleic acid molecules or 5′ to the sample nucleic acid segment of some,most, or typically each of the tagged nucleic acid molecules, and/oranother MIT can be located 3′ to the sample nucleic acid segment ofsome, most, or typically each of the tagged nucleic acid molecules. Inother embodiments, at least two MITs are located 5′ and/or 3′ to thesample nucleic acid segments of the tagged nucleic acid molecules, or 5′and/or 3′ to the sample nucleic acid segment of some, most, or typicallyeach of the tagged nucleic acid molecules. Two MITs can be added toeither the 5′ or 3′ by including both on the same polynucleotide segmentbefore attaching or by performing separate reactions. For example, PCRcan be performed with primers that bind to specific sequences within thesample nucleic acid molecules and include a region 5′ to thesequence-specific region that encodes two MITs. In some embodiments, atleast one copy of each MIT of the set of MITs is attached to a samplenucleic acid molecule, two copies of at least one MIT are each attachedto a different sample nucleic acid molecule, and/or at least two samplenucleic acid molecules with the same or substantially the same sequencehave at least one different MIT attached. A skilled artisan willidentify methods for attaching MITs to nucleic acid molecules of apopulation of nucleic acid molecules. For example, MITs can be attachedthrough ligation or appended 5′ to an internal sequence binding site ofa PCR primer and attached during a PCR reaction as discussed in moredetail herein.

After or while MITs are attached to sample nucleic acids to form taggednucleic acid molecules, the population of tagged nucleic acid moleculesare typically amplified to create a library of tagged nucleic acidmolecules. Methods for amplification to generate a library, includingthose particularly relevant to a high-throughput sequencing workflow,are known in the art. For example, such amplification can be a PCR-basedlibrary preparation. These methods can further include clonallyamplifying the library of tagged nucleic acid molecules onto one or moresolid supports using PCR or another amplification method such as anisothermal method. Methods for generating clonally amplified librariesonto solid supports in high-throughput sequencing sample preparationworkflows are known in the art. Additional amplification steps, such asa multiplex amplification reaction in which a subset of the populationof sample nucleic acid molecules are amplified, can be included inmethods for identifying sample nucleic acids provided herein as well.

In some embodiments, of methods provided herein a nucleotide sequence ofthe MITs and at least a portion of the sample nucleic acid moleculesegments of some, most, or all (e.g. at least 2, 3, 4, 5, 6, 7, 8, 9,10, 20, 25, 50, 75, 100, 150, 200, 250, 500, 1,000, 2,500, 5,000,10,000, 15,000, 20,000, 25,000, 50,000, 100,000, 1,000,000, 5,000,000,10,000,000, 25,000,000, 50,000,000, 100,000,000, 250,000,000,500,000,000, 1×10⁹, 1×10¹⁰, 1×10¹¹, 1×10¹², or 1×10¹³ tagged nucleicacid molecules or between 10, 20, 25, 30, 40, 50, 60, 70, 80, or 90% ofthe tagged nucleic acid molecules on the low end of the range and 20,25, 30, 40, 50, 60, 70, 80, or 90, 95, 96, 97, 98, 99, and 100% on thehigh end of the range) of the tagged nucleic acid molecules in thelibrary of tagged nucleic acid molecules is then determined. Thesequence of a first MIT and optionally a second MIT or more MITs onclonally amplified copies of a tagged nucleic acid molecule can be usedto identify the individual sample nucleic acid molecule that gave riseto the clonally amplified tagged nucleic acid molecule in the library.

In some embodiments, sequences determined from tagged nucleic acidmolecules sharing the same first and optionally the same second MIT canbe used to identify amplification errors by differentiatingamplification errors from true sequence differences at target loci inthe sample nucleic acid molecules. For example, in some embodiments, theset of MITs are double stranded MITs that, for example, can be a portionof a partially or fully double-stranded adapter, such as a Y-adapter. Inthese embodiments, for every starting molecule, a Y-adapter preparationgenerates 2 daughter molecule types, one in a + and one in a −orientation. A true mutation in a sample molecule should have bothdaughter molecules paired with the same 2 MITs in these embodimentswhere the MITs are a double stranded adapter, or a portion thereof.Additionally, when the sequences for the tagged nucleic acid moleculesare determined and bucketed by the MITs on the sequences into MITnucleic acid segment families, considering the MIT sequence andoptionally its complement for double-stranded MITs, and optionallyconsidering at least a portion of the nucleic acid segment, most, andtypically at least 75% in double-stranded MIT embodiments, of thenucleic acid segments in an MIT nucleic acid segment family will includethe mutation if the starting molecule that gave rise to the taggednucleic acid molecules had the mutation. In the event of anamplification (e.g. PCR) error, the worst-case scenario is that theerror occurs in cycle 1 of the 1^(st) PCR. In these embodiments, anamplification error will cause 25% of the final product to contain theerror (plus any additional accumulated error, but this should be <<1%).Therefore, in some embodiments, if an MIT nucleic acid segment familycontains at least 75% reads for a particular mutation or polymorphicallele, for example, it can be concluded that the mutation orpolymorphic allele is truly present in the sample nucleic acid moleculethat gave rise to the tagged nucleic acid molecule. The later an erroroccurs in a sample preparation process, the lower the proportion ofsequence reads that include the error in a set of sequencing readsgrouped (i.e. bucketed) by MITs into a paired MIT nucleic acid segmentfamily. For example, an error in a library preparation amplificationwill result in a higher percentage of sequences with the error in apaired MIT nucleic acid segment family, than an error in a subsequentamplification step in the workflow, such as a targeted multiplexamplification. An error in the final clonal amplification in asequencing workflow creates the lowest percentage of nucleic acidmolecules in a paired MIT nucleic acid segment family that includes theerror.

Any sequencing method can be used to carry out methods provided herein,especially those where multiple amplified copies of a sample nucleicacid molecule are used to determine the sequence of the sample nucleicacid molecule, or especially of a plurality of sample nucleic acidmolecules. Furthermore, tagged nucleic acid molecules yieldingsubstantially the same (e.g. at least 60%, 70%, 75%, 80%, 85%, 90%, 95,96, 97, 98, or 99% identical) sequence for their sample nucleic acidsegment and different MIT tags can be compared to determine thediversity of sequences in a population of sample nucleic acid molecules,and to differentiate true variants or mutations from errors generatedduring sample preparation, even at low allelic frequency. The methodembodiments of the present disclosure include methods for sequencing apopulation of sample nucleic acid molecules. Such methods are especiallyeffective for high-throughput sequencing methods. Such methods arediscussed in more detail herein.

The methods disclosed above and herein can be used for a number ofpurposes a skilled artisan would recognize in view of the presentdisclosure. For example, the methods can be used to determine thenucleic acid sequences of a population of nucleic acid molecules in asample, to identify a sample nucleic acid molecule that gave rise to atagged nucleic acid molecule, to identify a sample nucleic acid moleculefrom a population of sample nucleic acid molecules, to identifyamplification errors, to measure amplification bias, and to characterizethe mutation rates of polymerases. Further uses will be apparent to aperson skilled in the art. In these methods, after determining thesequences of the tagged nucleic acid segments, the nucleic acid segmentswith substantially the same nucleic acid segment sequence and the sametwo MIT tags or nucleic acid segments with substantially the same or thesame nucleic acid segment sequence and at least one different MIT tagcan be used for comparisons and further analysis.

Sample and Library Preparation

In the various embodiments provided herein, the sample can be from anatural or non-natural source. In some embodiments, the nucleic acidmolecules in the sample can be derived from a living organism or a cell.Any nucleic acid molecule can be used, for example, the sample caninclude genomic DNA covering a portion of or an entire genome, mRNA, ormiRNA from the living organism or cell. In certain respects, the totallengths of the entire genome or DNA sequences in a sample divided by theaverage size of the nucleic acid molecules can be used to determine thenumber of nucleic acid molecules in the sample to represent the entiregenome or all the DNA sequences. In further respects, this number can beused to determine the number of nucleic acid molecules that span atarget locus in the sample. A locus can include a single nucleotide or asegment of 1 to 1,000, 10,000, 100,000, 1 million, or more nucleotides.As nonlimiting examples, a locus can be a single nucleotidepolymorphism, an intron, or an exon. In some embodiments, a locus caninclude an insertion, deletion, or transposition. In some embodiments,the sample can include a blood, sera, or plasma sample. In someembodiments, the sample can include free floating DNA (e.g. circulatingcell-free tumor DNA or circulating cell-free fetal DNA) in a blood,sera, or plasma sample. In these embodiments, the sample is typicallyfrom an animal, such as a mammal or human, and is typically present infragments about 160 nucleotides in length. In some embodiments, thefree-floating DNA is isolated from blood using an EDTA-2Na tube afterremoval of cellular debris and platelets by centrifugation. The plasmasamples can be stored at −80° C. until the DNA is extracted using, forexample, QIAamp DNA Mini Kit (Qiagen, Hilden, Germany), (e.g. Hamakawaet al., Br J Cancer. 2015; 112:352-356). However, the sample can bederived from other sources and nucleic acid molecules from any organismcan be used for this method. In some embodiments, DNA derived frombacteria and/or viruses can be used to analyze true sequence variantswithin a mixed population, especially in environmental and biodiversitysampling.

Some embodiments disclosed herein are typically performed using samplenucleic acid molecules that were generated within and by a living cell.Such nucleic acid molecules are typically isolated directly from anatural source such as a cell or a bodily fluid without any in vitroamplification before the MITs are attached. Accordingly, the samplenucleic acid molecules are used directly in the reaction mixture toattach MITs. This circumvents the potential introduction ofamplification errors before the sample nucleic acid molecules aretagged. This in turn improves the ability to differentiate real sequencevariants from amplification errors. However, in some embodiments, samplenucleic acid molecules can be amplified before attaching the MITs. Askilled artisan will understand the best methods to use if amplificationis necessary before attaching MITs. For example, a high-fidelitypolymerase with proof-reading capability can be used for theamplification to help reduce the number of amplification errors thatcould be generated before the nucleic acid molecules have MITs attached.Furthermore, fewer cycles (e.g. between 2, 3, 4, and 5 cycles on the lowend of the range and 3, 4, 5, 6, 7, 8, 9, or 10 on the high end of therange) of amplification cycles can be employed.

In some embodiments, the nucleic acid molecules in the sample can befragmented to generate nucleic acid molecules of any chosen lengthbefore they are tagged with MITs. A skilled artisan will recognizemethods for performing such fragmentation and the chosen lengths asdiscussed in more detail herein. For example, the nucleic acids can befragmented using physical methods such as sonication, enzymatic methodssuch as digestion by DNase I or restriction endonucleases, or chemicalmethods such as applying heat in the presence of a divalent metalcation. Fragmentation can be performed such that a chosen size range ofnucleic acid molecules are left as discussed in more detail herein. Inother embodiments, nucleic acid molecules can be selected for specificsize ranges using methods known in the art.

After fragmentation, the sample nucleic acid molecules can have 5′and/or 3′ overhangs that need to be repaired before further librarypreparation. In some embodiments, before attaching MITs or other tags,the sample nucleic acid molecules with 5′ and 3′ overhangs can berepaired to generate blunt-ended sample nucleic acid molecules usingmethods known in the art. For example, in an appropriate buffer thepolymerase and exonuclease activities of the Klenow Large FragmentPolymerase can be used to fill in 5′ overhangs and remove 3′ overhangson the nucleic acid molecules. In some embodiments, a phosphate can beadded on the 5′ end of the repaired nucleic acid molecules usingPolynucleotide Kinase (PNK) and reaction conditions a skilled artisanwill understand. In further embodiments, a single nucleotide or multiplenucleotides can be added to one strand of a double stranded molecule togenerate a “sticky end.” For example, an adenosine (A) can be appendedon the 3′ ends of the nucleic acid molecules (A-tailing). In someembodiments, other sticky ends can be used other than an A overhang. Insome embodiments, other adaptors can be added, for example loopedligation adaptors. In any of the embodiments disclosed herein, none,all, or any combination of these modifications can be carried out.

Many kits and methods are known in the art for generating libraries ofnucleic acid molecules for subsequent sequencing. Kits especiallyadapted for preparing libraries from small nucleic acid fragments,especially circulating cell-free DNA, can be useful for practicingmethods provided herein. For example, the NEXTflex Cell Free kits (BiooScientific, Austin, Tex.) or the Natera Library Prep Kit (Natera, SanCarlos, Calif.). Such kits would typically be modified to includeadaptors that are customized for the amplification and sequencing stepsof the methods provided herein. Adaptor ligation can also be performedusing commercially available kits such as the ligation kit found in theAgilent SureSelect kit (Agilent, Santa Clara, Calif.).

Sample nucleic acid molecules are composed of naturally occurring ornon-naturally occurring ribonucleotides or deoxyribonucleotides linkedthrough phosphodiester linkages. Furthermore, sample nucleic acidmolecules are composed of a nucleic acid segment that is targeted forsequencing. Sample nucleic acid molecules can be or can include nucleicacid segments that are at least 20, 25, 50, 75, 100, 125, 150, 200, 250,300, 400, 500, 600, 700, 800, 900, or 1,000 nucleotides in length. Inany of the embodiments disclosed herein the sample nucleic acidmolecules or nucleic acid segments can be between 1, 2, 3, 4, 5, 6, 7,8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75, 100, 125,150, 200, 250, 300, 400, and 500 nucleotides in length on the low end ofthe range and 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75,100, 125, 150, 200, 250, 300, 400, 500, 1,000, 2,000, 3,000, 4,000,5,000, 6,000, 7,000, 8,000, 9,000, and 10,000 nucleotides in length onthe high end of the range. In some embodiments, the nucleic acidmolecules can be fragments of genomic DNA and can be between 1, 2, 3, 4,5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75,100, 125, 150, 200, 250, 300, 400, and 500 nucleotides in length on thelow end of the range and 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25,50, 75, 100, 125, 150, 200, 250, 300, 400, 500, 1,000, 2,000, 3,000,4,000, 5,000, 6,000, 7,000, 8,000, 9,000, and 10,000 nucleotides inlength on the high end of the range. For the sake of clarity, nucleicacids initially isolated from a living tissue, fluid, or cultured cells,can be much longer than sample nucleic acid molecules processed usingmethods herein. As discussed herein, for example, such initiallyisolated nucleic acid molecules can be fragmented to generate nucleicacid segments, before being used in the methods herein. In someembodiments, the nucleic acid molecules and nucleic acid segments can beidentical. The sample nucleic acid molecule or sample nucleic acidsegment can include a target locus that contains the nucleotide ornucleotides that are being queried, especially a single nucleotidepolymorphism or single nucleotide variant. In any of the disclosedembodiments, the target loci can be at least 1, 2, 3, 4, 5, 6, 7, 8, 9,10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75, 100, 125, 150,200, 250, 300, 400, 500, 600, 700, 800, 900, or 1,000 nucleotides inlength and include a portion of or the entirety of the sample nucleicacid molecule and/or the sample nucleic acid segment. In otherembodiments, the target loci can be between 1, 2, 3, 4, 5, 6, 7, 8, 9,10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75, 100, 125, 150,200, 250, 300, 400, and 500 nucleotides in length on the low end of therange and 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75, 100,125, 150, 200, 250, 300, 400, 500, 1,000, 2,000, 3,000, 4,000, 5,000,6,000, 7,000, 8,000, 9,000, and 10,000 nucleotides in length on the highend of the range. In some embodiments, the target loci on differentsample nucleic acid molecules can be at least 50%, 60%, 70%, 80%, 90%95%, 96%, 97%, 98%, 99%, 99.9%, or 100% identical. In some embodiments,the target loci on different sample nucleic acid molecules can share atleast 50%, 60%, 70%, 80%, 90% 95%, 96%, 97%, 98%, 99%, 99.9%, or 100%sequence identity.

In some embodiments, the entire sample nucleic acid molecule is a samplenucleic acid segment. For example, in certain embodiments where MITs areligated directly to the ends of sample nucleic acid molecules, orligated to a nucleic acid(s) ligated to the ends of sample nucleic acidmolecules, or ligated as part of primers that bind to sequences at thetermini of sample nucleic acid segments, or adapters, such as universaladapters added thereto, as discussed further herein, the entire nucleicacid molecule can be a sample nucleic acid segment. In otherembodiments, for example certain embodiments where MITs are attached tosample nucleic acid molecules as part of primers that target bindingsites internal to the termini of sample nucleic acid molecules, aportion of the sample nucleic acid molecule can be the sample nucleicacid segment that is targeted for downstream sequencing. For example, atleast 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or100% of a sample nucleic acid molecule can be a nucleic acid segment.

In some embodiments, sample nucleic acid molecules are a mixture ofnucleic acids isolated from a natural source, some sample nucleic acidmolecules having identical sequences, some having sequences sharing atleast 50%, 60%, 70%, 80%, 90%, 95%, 98%, or 99% sequence identity, andsome with less than 50%, 40%, 30%, 20%, 10%, or 5% sequence identityover between 20, 25, 50, 75, 100, 125, 150, 200, 250 nucleotides on thelow end of the range, and 50, 75, 100, 125, 150, 200, 250, 300, 400, or500 nucleotides on the high end of the range. Such sample nucleic acidmolecules can be nucleic acid samples isolated form tissues or fluids ofa mammal, such as a human, without enriching one sequence over another.In other embodiments, target sequences, for example, those from a geneof interest, can be enriched prior to performing methods providedherein.

In certain embodiments, some or all of the sample nucleic acid moleculesin the population of nucleic acid molecules can have identical, orsubstantially identical nucleic acid segments. Nucleic acid moleculescan be said to be substantially identical if the sequences of thenucleic acid segments share at least 90 percent sequence identity.Sample nucleic acid molecule, in certain illustrative examples, canshare a nucleic acid segment having 90%, 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%, or 99.9% sequence identity over between 20, 25, 50, 75,100, 125, 150, 200, 250 on the low end of the range, and 50, 75, 100,125, 150, 200, 250, 300, 400, or 500 nucleic on the high end of therange. Methods provided herein are effective at distinguishing samplenucleic acid molecules that share at least 90%, 95%, 96%, 97%, 985, 99%or even 100% sequence identity in a sample.

In some embodiments, the 5′ and 3′ ends of nucleic acid segmentsadjacent to attached MITs can be used to aid in identifying anddistinguishing sample nucleic acid molecules. Herein, these sequencesare referred to as fragment-specific insert ends. After attachment ofMITs as discussed elsewhere herein, the combination of MITs andfragment-specific insert ends can uniquely identify sample nucleic acidmolecules as a sufficiently high ratio of MITs to sample nucleic acidmolecules can be chosen such that the probability of two differentsample nucleic acid molecules having identical fragment-specific insertends and the same MIT(s) attached in the same orientation is exceedinglylow. For example, such that there is less than a 1, 0.5, 0.1, 0.05,0.01, 0.005, 0.001 or less probability. For example, using only MITs toidentify each sample nucleic acid molecule from a set of 200 MITs gives40,000 (200×200) possible combinations of identifiers. With theadditional information provided using fragment-specific insert ends, thenumber of possible combinations can increase quickly. For example,including 2 nucleotides from the 5′ and 3′ fragment-specific insert endsin the identification of the nucleic acid molecules increases the 40,000possible combinations to 10,240,000 possible combinations if eachnucleotide is equally likely in the dinucleotide sequence. The lengthsof the fragment-specific insert ends, when used in methods providedherein, can be between 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, and 30nucleotides on the low end of the range and 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,48, 49, and 50 nucleotides on the high end of the range. In someembodiments, the fragment-specific ends used in combination with MITs toidentify sample nucleic acid molecules are 1, 2, 3, or 4 nucleotides inlength.

In further embodiments, the determined sequences of thefragment-specific insert ends can be used to map each end of the nucleicacid molecule to specific locations in the genome (i.e. genomecoordinates) of the organism from which the sample was isolated. Themapped locations provide another identifier for each of the taggednucleic acid molecules. Mapping each end greatly increases the number ofidentifiers available for each tagged nucleic acid molecule. In theseembodiments, the mapped location of each end of the nucleic acidmolecule can be used in combination with the MITs to identify theindividual sample nucleic acid molecules that gave rise to the taggednucleic acid molecules. For instance, for a given target base inmononucleosomal circulating cell-free DNA (cfDNA), the 5′-side fragmentend can be anywhere between about 0 to 199 bases upstream. Likewise, the3′-side fragment end can be 0-199 bases downstream. Theoretically thiscould give 40,000 possible end combinations. In reality, most moleculesare between 100-200 bases in total length so the total number ofpossible combinations end up being around 15,000 (maximum, but not allcombinations occur at equal likelihood). This would mean 40,000 MITcombos×15,000 possible fragment ends=600,000,000 possible endcombinations. Furthermore, if a nucleic acid segment is mapped to thegenome a mutation in that segment or an allele of that segment can beidentified.

The total number of sample nucleic acid molecules can vary greatlydepending on the sample source and preparation as well as the needs ofthe method. For example, the total sample nucleic acid molecules can bebetween 1×10¹⁰, 2×10¹⁰, 2.5×10¹⁰, 5×10¹⁰ and 1×10¹¹ on the low end ofthe range and 5×10¹⁰, 1×10¹¹, 2×10¹¹, 2.5×10¹¹, 5×10¹¹, 1×10¹², 2×10¹²,2.5×10¹², 5×10¹², and 1×10¹³ nucleic acid molecules on the high end ofthe range. For example, 10,000 copies of the genome from humancirculating cell-free DNA could be composed of 2×10¹¹ total samplenucleic acid molecules since mononucleosomal cfDNA is approximately 100to 200 bp nucleic acid fragments that have highly variable fragmentationpatterns (3,000,000,000 bp/genome copy×10,000 genome copies/150bp/sample nucleic acid molecule=2×10¹¹ sample nucleic acid molecules).

In some embodiments, provided herein, the total number of sample nucleicacid molecules can include between 50, 100, 200, 250, 500, 750, 1,000,2,000, 2,500, 5,000, and 10,000 copies of the human genome on the lowend of the range, and 1,000, 2,000, 2,5000, 5,000, 10,000, 20,000,25,000, 50,000, and 100,000 copies of the human genome on the high endof the range. In other embodiments, the total number of sample nucleicacid molecules is the number of nucleic acid molecules of between 100and 500 nucleotides in length, for example, 200 nucleotides in 1, 2,2.5, 3, 4, or 5 nM on the low end and 2.5, 3, 4, 5, 10, 20 or 25 nM ofcfDNA on the high end of the range.

Diversity of a set or a population of nucleic acid molecules is thenumber of unique sequences among the nucleic acid molecules in the setor population. The diversity of sample nucleic acid molecules is thenumber of unique sequences among sample nucleic acid molecules. It iscommon to have more than 1 copy of an identical or near identicalnucleic acid sequence in a sample even when nucleic acid molecules in asample have not been subjected to amplification. Current nucleic acidsample preparation and DNA isolation procedures typically result in manycopies of every nucleic acid molecule in the sample.

In any of the embodiments disclosed herein the diversity of nucleotidesequences of the sample nucleic acid molecules in the population can bebetween 100, 1,000, 10,000, 1×10⁵ 1×10⁶, and 1×10⁷ different nucleicacid sequences on the low end of the range, and 1×10⁵ 1×10⁶, and 1×10⁷,1×10⁸, 1×10⁹, and 1×10¹⁰ different nucleotide sequences on the high endof the range. In some embodiments, the diversity of nucleotide sequencesin the population of sample nucleic acid molecules is between 1×10⁶,5×10⁶, and 1×10⁷ different nucleic acid sequences on the low end of therange, and 1×10⁷, 1×10⁸, 1×10⁹, and 1×10¹⁰, different nucleotidesequences on the high end of the range.

For a human cfDNA sample, since there are about 3 billion nucleotides inthe human genome, since the nucleic acid fragment size is about 150nucleotides, and since the fragmentation pattern is not random but notfixed either, there are between about 20 million (3 billion/150) andabout 3 billion different nucleic acid fragments in a human cfDNAsample. Accordingly, in some embodiments, the sample is a human cfDNAsample, such as, for example, a purified sample, or a serum or plasmasample, and the diversity of the sample is between 20 million and 3billion.

Sample nucleic acid molecules can be of approximately the same length incertain embodiments of the present disclosure. For example, the samplenucleic acid molecules can be about 200 nucleotides, for example forcirculating cell-free DNA samples, or between 50, 75, 100, 125 or 150nucleotides on the low end of the range and 150, 200, 250, or 300nucleotides in length on the high end for certain samples, for exampleblood, sera, or plasma samples that include circulating cell-free DNA.

In other embodiments, sample nucleic acid molecules can be differentranges of starting lengths. The lengths of the sample nucleic acidmolecules with or without fragmentation can be any size appropriate forthe subsequent method steps. For example, sample nucleic acid moleculescan be between at least 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,22, 23, 24, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 125, 150, 175,200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1,000, 1,250,1,500, 1,750, 2,000, 2,500, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000,9,000, and 10,000 nucleotides on the low end and 15, 16, 17, 18, 19, 20,21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 125, 150,175, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1,000,1,250, 1,500, 1,750, 2,000, 2,500, 3,000, 4,000, 5,000, 6,000, 7,000,8,000, 9,000, 10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000,17,000, 18,000, 19,000, 20,000, 25,000, 30,000, 40,000, 50,000, 60,000,70,000, 80,000, 90,000, and 100,000 nucleotides on the high end.

In certain respects, the chosen size range of starting lengths of thesample nucleic acid segments molecules is dependent on the method ofattachment. Longer ranges of nucleic acid molecule lengths are chosen ifPCR is used as they increase the probability of two primers binding tothe same nucleic acid molecule. Shorter ranges of nucleic acid moleculelengths are chosen if ligation is used as they reduce the length of theamplicons generated by PCR in later steps in the method, especially ifPCR is performed using universal primers that bind outside the nucleicacid segments. Therefore, when using ligation to attach the MITs, thesample nucleic acid molecules will generally be shorter than when usingPCR to attach the MITs. For example, in some embodiments, the samplenucleic acid molecules are between 10, 11, 12, 13, 14, 15, 16, 17, 18,19, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100,110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 225, 250, 300, 350,400, 450, 500, 600, 700, 800, 900, and 1,000 nucleotides on the low endand 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 55, 60,65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180,190, 200, 225, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1,000,1,100, 1,200, 1,300, 1,400, 1,500, 1,600, 1,700, 1,800, 1,900, 2,000,2,500, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, and 10,000nucleotides on the high end and the MITs are attached by ligation. Incertain embodiments, the sample nucleic acid molecules are between 50,55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160,170, 180, 190, 200, 225, 250, 300, 350, 400, 450, 500, 600, 700, 800,900, 1,000, 1,100, 1,200, 1,300, 1,400, 1,500, 1,600, 1,700, 1,800,1,900, 2,000, 2,500, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000,and 10,000 nucleotides on the low end and 100, 110, 120, 130, 140, 150,160, 170, 180, 190, 200, 225, 250, 300, 350, 400, 450, 500, 600, 700,800, 900, 1,000, 1,100, 1,200, 1,300, 1,400, 1,500, 1,600, 1,700, 1,800,1,900, 2,000, 2,500, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000,10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000, 17,000, 18,000,19,000, 20,000, 25,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000,90,000, and 100,000 nucleotides on the high end and the MITs areattached by PCR.

In some embodiments, the nucleic acid molecules in the sample can besynthesized using a machine. In some embodiments, the nucleic acidmolecules are generated by a living cell. In some embodiments, nucleicacid molecules generated by a living cell and nucleic acid moleculessynthesized using a machine can be combined and used as the samplenucleic acid molecules. This combination may be beneficial forquantitation purposes. In some embodiments, the sample nucleic acidmolecules have not been amplified in vitro.

MITs and MIT Reaction Mixtures

The step of attaching MITs to sample nucleic acid molecules or nucleicacid segments in methods provided herein, typically includes forming areaction mixture. The reaction mixtures formed during such methods canthemselves be individual aspects of the present disclosure. Reactionmixtures provided herein can include sample nucleic acid molecules, asdisclosed in detail herein, and a set of MITs, as disclosed in detailherein, wherein the total number of nucleic acid molecules in the sampleis greater than the diversity of MITs in the set of MITs. In someembodiments, the total number of nucleic acid molecules in the sample isalso greater than the diversity of possible combinations of attachedMITs.

In some embodiments disclosed herein, the ratio of the total number ofthe sample nucleic acid molecules to the diversity of the MITs in theset of MITs or the diversity of the possible combinations of attachedMITs using the set of MITs can be between 10:1, 20:1, 30:1, 40:1, 50:1,60:1, 70:1, 80:1, 90:1, 100:1 200:1, 300:1, 400:1, 500:1, 600:1, 700:1,800:1, 900:1, 1,000:1, 2,000:1, 3,000:1, 4,000:1, 5,000:1, 6,000:1,7,000:1, 8,000:1, 9,000:1, 10,000:1, 15,000:1, 20,000:1, 25,000:1,30,000:1, 40,000:1, 50,000:1, 60,000:1, 70,000:1, 80,000:1, 90,000:1,100,000:1, 200,000:1, 300,000:1, 400,000:1, 500,000:1, 600,000:1,700,000:1, 800,000:1, 900,000:1, and 1,000,000:1 on the low end of therange and 100:1 200:1, 300:1, 400:1, 500:1, 600:1, 700:1, 800:1, 900:1,1,000:1, 2,000:1, 3,000:1, 4,000:1, 5,000:1, 6,000:1, 7,000:1, 8,000:1,9,000:1, 10,000:1, 15,000:1, 20,000:1, 25,000:1, 30,000:1, 40,000:1,50,000:1, 60,000:1, 70,000:1, 80,000:1, 90,000:1, 100,000:1, 200,000:1,300,000:1, 400,000:1, 500,000:1, 600,000:1, 700,000:1, 800,000:1,900,000:1, 1,000,000:1, 2,000,000:1, 3,000,000:1, 4,000,000:1,5,000,000:1, 6,000,000:1, 7,000,000:1, 8,000,000:1, 9,000,000:1,10,000,000:1, 50,000,000:1, 100,000,000:1, and 1,000,000,000:1 on thehigh end of the range.

In some embodiments, the sample is a human cfDNA sample. In such amethod, as disclosed herein, the diversity is between about 20 millionand about 3 billion. In these embodiments, the ratio of the total numberof sample nucleic acid molecules to the diversity of the set of MITs canbe between 100,000:1, 1×10⁶:1, 1×10⁷:1, 2×10⁷:1, and 2.5×10⁷:1 on thelow end of the range and 2×10⁷:1, 2.5×10⁷:1, 5×10⁷:1, 1×10⁸:1,2.5×10⁸:1, 5×10⁸:1, and 1×10⁹:1 on the high end of the range.

In some embodiments, the diversity of possible combinations of attachedMITs using the set of MITs is preferably greater than the total numberof sample nucleic acid molecules that span a target locus. For example,if there are 100 copies of the human genome that have all beenfragmented into 200 bp fragments such that there are approximately15,000,000 fragments for each genome, then it is preferable that thediversity of possible combinations of MITs be greater than 100 (numberof copies of each target locus) but less than 1,500,000,000 (totalnumber of nucleic acid molecules). For example, the diversity ofpossible combinations of MITs can be greater than 100 but much less than1,500,000,000, such as 200, 300, 400, 500, 600, 700, 800, 900, or 1,000possible combinations of attached MITs. While the diversity of MITs inthe set of MITs is less than the total number of nucleic acid molecules,the total number of MITs in the reaction mixture is in excess of thetotal number of nucleic acid molecules or nucleic acid molecule segmentsin the reaction mixture. For example, if there are 1,500,000,000 totalnucleic acid molecules or nucleic acid molecule segments, then therewill be more than 1,500,000,000 total MIT molecules in the reactionmixture. In some embodiments, the ratio of the diversity of MITs in theset of MITs can be lower than the number of nucleic acid molecules in asample that span a target locus while the diversity of the possiblecombinations of attached MITs using the set of MITs can be greater thanthe number of nucleic acid molecules in the sample that span a targetlocus. For example, the ratio of the number of nucleic acid molecules ina sample that span a target locus to the diversity of MITs in the set ofMITs can be at least 10:1, 25:1, 50:1, 100:1, 125:1, 150:1, or 200:1 andthe ratio of the diversity of the possible combinations of attached MITsusing the set of MITs to the number of nucleic acid molecules in thesample that span a target locus can be at least 1.01:1, 1.1:1, 2:1, 3:1,4:1, 5:1, 6:1, 7:1, 8:1, 9:1, 10:1, 20:1, 25:1, 50:1, 100:1, 250:1,500:1, or 1,000:1.

Typically, the diversity of MITs in the set of MITs is less than thetotal number of sample nucleic acid molecules that span a target locuswhereas the diversity of the possible combinations of attached MITs isgreater than the total number of sample nucleic acid molecules that spana target locus. In embodiments where 2 MITs are attached to samplenucleic acid molecules, the diversity of MITs in the set of MITs is lessthan the total number of sample nucleic acid molecules that span atarget locus but greater than the square root of the total number ofsample nucleic acid molecules that span a target locus. In someembodiments, the diversity of MITs is less than the total number ofsample nucleic acid molecules that span a target locus but 1, 2, 3, 4,or 5 more than the square root of the total number of sample nucleicacid molecules that span a target locus. Thus, although the diversity ofMITs is less than the total number of sample nucleic acid molecules thatspan a target locus, the total number of combinations of any 2 MITs isgreater than the total number of sample nucleic acid molecules that spana target locus. The diversity of MITs in the set is typically less thanone half the number of sample nucleic acid molecules than span a targetlocus in samples with at least 100 copies of each target locus. In someembodiments, the diversity of MITs in the set can be at least 1, 2, 3,4, or 5 more than the square root of the total number of sample nucleicacid molecules that span a target locus but less than ⅕, 1/10, 1/20,1/50, or 1/100 the total number of sample nucleic acid molecules thatspan a target locus. For samples with between 2,000 and 1,000,000 samplenucleic acid molecules that span a target locus, the number of MITs inthe set does not exceed 1,000. For example, in a sample with 10,000copies of the genome in a genomic DNA sample such as a circulatingcell-free DNA sample such that the sample has 10,000 sample nucleic acidmolecules that span a target locus, the diversity of MITs can be between101 and 1,000, or between 101 and 500, or between 101 and 250. In someembodiments, the diversity of MITs in the set of MITs can be between thesquare root of the total number of sample nucleic acid molecules thatspan a target locus and 1, 10, 25, 50, 100, 125, 150, 200, 250, 300,400, 500, 600, 700, 800, 900, or 1,000 less than the total number ofsample nucleic acid molecules that span a target locus. In someembodiments, the diversity of MITs in the set of MITs can be between0.01%, 0.05%, 0.1%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%,35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, and 80% of the number ofsample nucleic acid molecules that span a target locus on the low end ofthe range and 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%,45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%,and 99% of the number of sample nucleic acid molecules that span atarget locus on the high end of the range.

In some embodiments, the ratio of the total number of MITs in thereaction mixture to the total number of sample nucleic acid molecules inthe reaction mixture can be between 1.01, 1.1:1, 2:1, 3:1, 4:1, 5:1,6:1, 7:1, 8:1, 9:1, 10:1, 25:1 50:1, 100:1, 200:1, 300:1, 400:1, 500:1,600:1, 700:1, 800:1, 900:1, 1,000:1, 2,000:1, 3,000:1, 4,000:1, 5,000:1,6,000:1, 7,000:1, 8,000:1, 9,000:1, and 10,000:1 on the low end of therange and 25:150:1, 100:1, 200:1, 300:1, 400:1, 500:1, 600:1, 700:1,800:1, 900:1, 1,000:1, 2,000:1, 3,000:1, 4,000:1, 5,000:1, 6,000:1,7,000:1, 8,000:1, 9,000:1, 10,000:1, 15,000:1, 20,000:1, 25,000:1,30,000:1, 40,000:1, and 50,000:1 on the high end of the range. In someembodiments, the total number of MITs in the reaction mixture is atleast 50%, 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98% 99%, or 99.9% of thetotal number of sample nucleic acid molecules in the reaction mixture.In other embodiments, the ratio of the total number of MITs in thereaction mixture to the total number of sample nucleic acid molecules inthe reaction mixture can be at least enough MITs for each sample nucleicacid molecule to have the appropriate number of MITs attached, i.e. 2:1for 2 MITs being attached, 3:1 for 3 MITs, 4:1 for 4 MITs, 5:1 for 5MITs, 6:1 for 6 MITs, 7:1 for 7 MITs, 8:1 for 8 MITs, 9:1 for 0 MITs,and 10:1 for 10 MITs.

In some embodiments, the ratio of the total number of MITs withidentical sequences in the reaction mixture to the total number ofnucleic acid segments in the reaction mixture can be between 0.1:1,0.2:1, 0.3:1, 0.4:1, 0.5:1, 0.6:1, 0.7:1, 0.8:1, 0.9:1, 1:1, 1.1:1,1.2:1, 1.3:1, 1.4:1, 1.5:1, 1.6:1, 1.7:1, 1.8:1, 1.9:1, 2:1, 2.25:1,2.5:1, 2.75:1, 3:1, 3.5:1, 4:1, 4.5:1, and 5:1 on the low end of therange and 0.5:1, 0.6:1, 0.7:1, 0.8:1, 0.9:1, 1:1, 1.1:1, 1.2:1, 1.3:1,1.4:1, 1.5:1, 1.6:1, 1.7:1, 1.8:1, 1.9:1, 2:1, 2.25:1, 2.5:1, 2.75:1,3:1, 3.5:1, 4:1, 4.5:1, 5:1, 6:1, 7:1, 8:1, 9:1, 10:1, 20:1, 30:1, 40:1,50:1, 60:1, 70:1, 80:1, 90:1, and 100:1 on the high end of the range.

The set of MITs can include, for example, at least three MITs or between10 and 500 MITs. As discussed herein in some embodiments, nucleic acidmolecules from the sample are added directly to the attachment reactionmixture without amplification. These sample nucleic acid molecules canbe purified from a source, such as a living cell or organism, asdisclosed herein, and then MITs can be attached without amplifying thenucleic acid molecules. In some embodiments, the sample nucleic acidmolecules or nucleic acid segments can be amplified before attachingMITs. As discussed herein, in some embodiments, the nucleic acidmolecules from the sample can be fragmented to generate sample nucleicacid segments. In some embodiments, other oligonucleotide sequences canbe attached (e.g. ligated) to the ends of the sample nucleic acidmolecules before the MITs are attached.

In some embodiments disclosed herein the ratio of sample nucleic acidmolecules, nucleic acid segments, or fragments that include a targetlocus to MITs in the reaction mixture can be between 1.01:1, 1.05,1.1:1, 1.2:1 1.3:1, 1.4:1, 1.5:1, 1.6:1, 1.7:1, 1.8:1, 1.9:1, 2:1,2.5:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, 9:1, 10:1, 15:1, 20:1, 25:1, 30:1,35:1, 40:1, 45:1, and 50:1 on the low end and 5:1, 6:1, 7:1, 8:1, 9:1,10:1, 15:1, 20:1, 25:1, 30:1, 35:1, 40:1, 45:1, 50:1 60:1, 70:1, 80:1,90:1, 100:1, 125:1, 150:1, 175:1, 200:1, 300:1, 400:1 and 500:1 on thehigh end. For example, in some embodiments, the ratio of sample nucleicacid molecules, nucleic acid segments, or fragments with a specifictarget locus to MITs in the reaction mixture is between 5:1, 6:1, 7:1,8:1, 9:1, 10:1, 15:1, 20:1, 25:1, 30:1, 35:1, 40:1, 45:1, and 50:1 onthe low end and 20:1, 25:1, 30:1, 35:1, 40:1, 45:1, 50:1, 60:1, 70:1,80:1, 90:1, 100:1, and 200:1 on the high end. In some embodiments, theratio of sample nucleic acid molecules or nucleic acid segments to MITsin the reaction mixture can be between 25:1, 30:1, 35:1, 40:1, 45:1,50:1 on the low end and 50:1 60:1, 70:1, 80:1, 90:1, 100:1 on the highend. In some embodiments, the diversity of the possible combinations ofattached MITs can be greater than the number of sample nucleic acidmolecules, nucleic acid segments, or fragments that span a target locus.For example, in some embodiments, the ratio of the diversity of thepossible combinations of attached MITs to the number of sample nucleicacid molecules, nucleic acid segments, or fragments that span a targetlocus can be at least 1.01, 1.1:1, 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1,9:1, 10:1, 20:1, 25:1, 50:1, 100:1, 250:1, 500:1, or 1,000:1.

Reaction mixtures for tagging nucleic acid molecules with MITs (i.e.attaching nucleic acid molecules to MITs), as provided herein, caninclude additional reagents in addition to a population of samplenucleic acid molecules and a set of MITs. For example, the reactionmixtures for tagging can include a ligase or polymerase with suitablebuffers at an appropriate pH, adenosine triphosphate (ATP) forATP-dependent ligases or nicotinamide adenine dinucleotide forNAD-dependent ligases, deoxynucleoside triphosphates (dNTPs) forpolymerases, and optionally molecular crowding reagents such aspolyethylene glycol. In certain embodiments the reaction mixture caninclude a population of sample nucleic acid molecules, a set of MITs,and a polymerase or ligase, wherein the ratio of the number of samplenucleic acid molecules, nucleic acid segments, or fragments with aspecific target locus to the number of MITs in the reaction mixture canbe any of the ratios disclosed herein, for example between 2:1 and100:1, or between 10:1 and 100:1 or between 25:1 and 75:1, or is between40:1 and 60:1, or between 45:1 and 55:1, or between 49:1 and 51:1.

In some embodiments disclosed herein the number of different MITs (i.e.diversity) in the set of MITs can be between 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 60, 70,80, 90, 100, 125, 150, 175, 200, 250, 300, 350, 400, 450, 500, 600, 700,800, 900, 1,000, 1,500, 2,000, 2,500, and 3,000 MITs with differentsequences on the low end and 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 125,150, 175, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1,000,2,000, 3,000, 4,000, and 5,000 MITs with different sequences on the highend. For example, the diversity of different MITs in the set of MITs canbe between 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, and 100 differentMIT sequences on the low end and 50, 60, 70, 80, 90, 100, 125, 150, 175,200, 250, and 300 different MIT sequences on the high end. In someembodiments, the diversity of different MITs in the set of MITs can bebetween 50, 60, 70, 80, 90, 100, 125, and 150 different MIT sequences onthe low end and 100, 125, 150, 175, 200, and 250 different MIT sequenceson the high end. In some embodiments, the diversity of different MITs inthe set of MITs can be between 3 and 1,000, or 10 and 500, or 50 and 250different MIT sequences. In some embodiments, the diversity of possiblecombinations of attached MITs using the set of MITs can be between 4, 5,6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50, 75, 100, 150, 200, 250, 300,400, 500, and 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000,9,000, 10,000, 20,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000,90,000, 100,000, 250,000, 500,000, 1,000,000, possible combinations ofattached MITs on the low end of the range and 10, 15, 20, 25, 30, 40,50, 75, 100, 150, 200, 250, 300, 400, 500, 1,000, 2,000, 3,000, 4,000,5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 20,000, 30,000, 40,000,50,000, 60,000, 70,000, 80,000, 90,000, 100,000, 250,000, 500,000,1,000,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000, 6,000,000,7,000,000, 8,000,000, 9,000,000, and 10,000,000 possible combinations ofattached MITs on the high end of the range.

The MITs in the set of MITs are typically all the same length. Forexample, in some embodiments, the MITs can be any length between 2, 3,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20nucleotides on the low end and 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, and 30nucleotides on the high end. In certain embodiments, the MITs are anylength between 3, 4, 5, 6, 7, or 8 nucleotides on the low end and 5, 6,7, 8, 9, 10, or 11 nucleotides on the high end. In some embodiments, thelengths of the MITs can be any length between 4, 5, or 6, nucleotides onthe low end and 5, 6, or 7 nucleotides on the high end. In someembodiments, the length of the MITs is 5, 6, or 7 nucleotides.

As will be understood, a set of MITs typically includes many identicalcopies of each MIT member of the set. In some embodiments, a set of MITsincludes between 10, 20, 25, 30, 40, 50, 100, 500, 1,000, 10,000,50,000, and 100,000 times more copies on the low end of the range, and100, 500, 1,000, 10,000, 50,000, 100,000, 250,000, 500,000 and 1,000,000more copies on the high end of the range, than the total number ofsample nucleic acid molecules that span a target locus. For example, ina human circulating cell-free DNA sample isolated from plasma, there canbe a quantity of DNA fragments that includes, for example, 1,000-100,000circulating fragments that span any target locus of the genome. Incertain embodiments, there are no more than 1/10, ¼, ½, or ¾ as manycopies of any given MIT as total unique MITs in a set of MITs. Betweenmembers of the set, there can be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10differences between any sequence and the rest of the sequences. In someembodiments, the sequence of each MIT in the set differs from all theother MITs by at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides. Toreduce the chance of misidentifying an MIT, the set of MITs can bedesigned using methods a skilled artisan will recognize, such as takinginto consideration the Hamming distances between all the MITs in the setof MITs. The Hamming distance measures the minimum number ofsubstitutions required to change one string, or nucleotide sequence,into another. Here, the Hamming distance measures the minimum number ofamplification errors required to transform one MIT sequence in a setinto another MIT sequence from the same set. In certain embodiments,different MITs of the set of MITs have a Hamming distance of less than1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 between each other.

In certain embodiments, a set of isolated MITs as provided herein is oneembodiment of the present disclosure. The set of isolated MITs can be aset of single stranded, or partially, or fully double stranded nucleicacid molecules, wherein each MIT is a portion of, or the entire, nucleicacid molecule of the set. In certain examples, provided herein is a setof Y-adapter (i.e. partially double-stranded) nucleic acids that eachinclude a different MIT. The set of Y-adapter nucleic acids can each beidentical except for the MIT portion. Multiple copies of the sameY-adapter MIT can be included in the set. The set can have a number anddiversity of nucleic acid molecules as disclosed herein for a set ofMITs. As a non-limiting example, the set can include 2, 5, 10, or 100copies of between 50 and 500 MIT-containing Y-adapters, with each MITsegment between 4 and 8 nucleic acids in length and each MIT segmentdiffering from the other MIT segments by at least 2 nucleotides, butcontain identical sequences other than the MIT sequence. Further detailsregarding Y-adapter portion of the set of Y-adapters is provided herein.

In other embodiments, a reaction mixture that includes a set of MITs anda population of sample nucleic acid molecules is one embodiment of thepresent disclosure. Furthermore, such a composition can be part ofnumerous methods and other compositions provided herein. For example, infurther embodiments, a reaction mixture can include a polymerase orligase, appropriate buffers, and supplemental components as discussed inmore detail herein. For any of these embodiments, the set of MITs caninclude between 25, 50, 100, 200, 250, 300, 400, 500, or 1,000 MITs onthe low end of the range, and 100, 200, 250, 300, 400, 500, 1,000,1,500, 2,000, 2,500, 5,000, 10,000, or 25,000 MITs on the high end ofthe range. For example, in some embodiments, a reaction mixture includesa set of between 10 and 500 MITs.

Attaching the MITs

Molecular Index Tags (MITs) as discussed in more detail herein can beattached to sample nucleic acid molecules in the reaction mixture usingmethods that a skilled artisan will recognize. In some embodiments, theMITs can be attached alone, or without any additional oligonucleotidesequences. In some embodiments, the MITs can be part of a largeroligonucleotide that can further include other nucleotide sequences asdiscussed in more detail herein. For example, the oligonucleotide canalso include primers specific for nucleic acid segments or universalprimer binding sites, adapters such as sequencing adapters such asY-adapters, library tags, ligation adapter tags, and combinationsthereof. A skilled artisan will recognize how to incorporate varioustags into oligonucleotides to generate tagged nucleic acid moleculesuseful for sequencing, especially high-throughput sequencing. The MITsof the present disclosure are advantageous in that they are more readilyused with additional sequences, such as Y-adapter and/or universalsequences because the diversity of nucleic acid molecules is less, andtherefore they can be more easily combined with additional sequences onan adapter to yield a smaller, and therefore more cost effective set ofMIT-containing adapters.

In some embodiments, the MITs are attached such that one MIT is 5′ tothe sample nucleic acid segment and one MIT is 3′ to the sample nucleicacid segment in the tagged nucleic acid molecule. For example, in someembodiments, the MITs can be attached directly to the 5′ and 3′ ends ofthe sample nucleic acid molecules using ligation. In some embodimentsdisclosed herein, ligation typically involves forming a reaction mixturewith appropriate buffers, ions, and a suitable pH in which thepopulation of sample nucleic acid molecules, the set of MITs, adenosinetriphosphate, and a ligase are combined. A skilled artisan willunderstand how to form the reaction mixture and the various ligasesavailable for use. In some embodiments, the nucleic acid molecules canhave 3′ adenosine overhangs and the MITs can be located ondouble-stranded oligonucleotides having 5′ thymidine overhangs, such asdirectly adjacent to a 5′ thymidine.

In further embodiments, MITs provided herein can be included as part ofY-adapters before they are ligated to sample nucleic acid molecules.Y-adapters are well-known in the art and are used, for example, to moreeffectively provide primer binding sequences to the two ends of thenucleic acid molecules before high-throughput sequencing. Y-adapters areformed by annealing a first oligonucleotide and a second oligonucleotidewhere a 5′ segment of the first oligonucleotide and a 3′ segment of thesecond oligonucleotide are complementary and wherein a 3′ segment of thefirst oligonucleotide and a 5′ segment of the second oligonucleotide arenot complementary. In some embodiments, Y-adapters include abase-paired, double-stranded polynucleotide segment and an unpaired,single-stranded polynucleotide segment distal to the site of ligation.The double-stranded polynucleotide segment can be between 3, 4, 5, 6, 7,8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 nucleotides inlength on the low end of the range and 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, and 30nucleotides in length on the high end of the range. The single-strandedpolynucleotide segments on the first and second oligonucleotides can bebetween 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or20 nucleotides in length on the low end of the range and 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26,27, 28, 29, and 30 nucleotides in length on the high end of the range.In these embodiments, MITs are typically double stranded sequences addedto the ends of Y-adapters, which are ligated to sample nucleic acidsegments to be sequenced. Exemplary Y-adapters are illustrated inFIG. 1. In some embodiments, the non-complementary segments of the firstand second oligonucleotides can be different lengths.

In some embodiments, double-stranded MITs attached by ligation will havethe same MIT on both strands of the sample nucleic acid molecule. Incertain respects the tagged nucleic acid molecules derived from thesetwo strands will be identified and used to generate paired MIT families.In downstream sequencing reactions, where single stranded nucleic acidsare typically sequenced, an MIT family can be identified by identifyingtagged nucleic acid molecules with identical or complementary MITsequences. In these embodiments, the paired MIT families can be used toverify the presence of sequence differences in the initial samplenucleic acid molecule as discussed herein.

In some embodiments, as illustrated in FIG. 2, MITs can be attached tothe sample nucleic acid segment by being incorporated 5′ to forwardand/or reverse PCR primers that bind sequences in the sample nucleicacid segment. In some embodiments, the MITs can be incorporated intouniversal forward and/or reverse PCR primers that bind universal primerbinding sequences previously attached to the sample nucleic acidmolecules. In some embodiments, the MITs can be attached using acombination of a universal forward or reverse primer with a 5′ MITsequence and a forward or reverse PCR primer that bind internal bindingsequences in the sample nucleic acid segment with a 5′ MIT sequence.After 2 cycles of PCR, sample nucleic acid molecules that have beenamplified using both the forward and reverse primers with incorporatedMIT sequences will have MITs attached 5′ to the sample nucleic acidsegments and 3′ to the sample nucleic acid segments in each of thetagged nucleic acid molecules. In some embodiments, the PCR is done for2, 3, 4, 5, 6, 7, 8, 9, or 10 cycles in the attachment step.

In some embodiments disclosed herein the two MITs on each tagged nucleicacid molecule can be attached using similar techniques such that bothMITs are 5′ to the sample nucleic acid segments or both MITs are 3′ tothe sample nucleic acid segments. For example, two MITs can beincorporated into the same oligonucleotide and ligated on one end of thesample nucleic acid molecule or two MITs can be present on the forwardor reverse primer and the paired reverse or forward primer can have zeroMITs. In other embodiments, more than two MITs can be attached with anycombination of MITs attached to the 5′ and/or 3′ locations relative tothe nucleic acid segments.

As discussed herein, other sequences can be attached to the samplenucleic acid molecules before, after, during, or with the MITs. Forexample, ligation adapters, often referred to as library tags orligation adaptor tags (LTs), appended, with or without a universalprimer binding sequence to be used in a subsequent universalamplification step. In some embodiments, the length of theoligonucleotide containing the MITs and other sequences can be between5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 29, 20, 21, 22, 23,24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85,90, 95, and 100 nucleotides on the low end of the range and 10, 11, 12,13, 14, 15, 16, 17, 18, 29, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130,140, 150, 160, 170, 180, 190, and 200 nucleotides on the high end of therange. In certain respects the number of nucleotides in the MITsequences can be a percentage of the number of nucleotides in the totalsequence of the oligonucleotides that include MITs. For example, in someembodiments, the MIT can be at most 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%,11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 25%, 30%, 35%, 40%,45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 100% of thetotal nucleotides of an oligonucleotide that is ligated to a samplenucleic acid molecule.

After attaching MITs to the sample nucleic acid molecules through aligation or PCR reaction, it may be necessary to clean up the reactionmixture to remove undesirable components that could affect subsequentmethod steps. In some embodiments, the sample nucleic acid molecules canbe purified away from the primers or ligases. In other embodiments, theproteins and primers can be digested with proteases and exonucleasesusing methods known in the art.

After attaching MITs to the sample nucleic acid molecules, a populationof tagged nucleic acid molecules is generated, itself formingembodiments of the present disclosure. In some embodiments, the sizeranges of the tagged nucleic acid molecules can be between 10, 20, 30,40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 250, 300, 400, and 500nucleotides on the low end of the range and 100, 125, 150, 175, 200,250, 300, 400, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000, and5,000 nucleotides on the high end of the range.

Such a population of tagged nucleic acid molecules can include between5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35,40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140,150, 160, 170, 180, 190, 200, 225, 250, 300, 350, 400, 450, 500, 600,700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000,9,000, 10,000, 15,000, 20,000, 30,000, 40,000, 50,000, 100,000, 200,000,300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000,1,000,000, 1,250,000, 1,500,000, 2,000,000, 2,500,000, 3,000,000,4,000,000, 5,000,000, 10,000,000, 20,000,000, 30,000,000, 40,00,000,50,000,000, 50,000,000, 100,000,000, 200,000,000, 300,000,000,400,000,000, 500,000,000, 600,000,000, 700,000,000, 800,000,000,900,000,000, and 1,000,000,000 tagged nucleic acid molecules on the lowend of the range and 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, 100,150, 200, 250, 300, 400, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000,4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 15,000, 20,000,30,000, 40,000, 50,000, 100,000, 200,000, 300,000, 400,000, 500,000,600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000,2,000,000, 2,500,000, 3,000,000, 4,000,000, 5,000,000, 6,000,000,7,000,000, 8,000,000, 9,000,000, 10,000,000, 20,000,000, 30,000,000,40,00,000, 50,000,000, 100,000,000, 200,000,000, 300,000,000,400,000,000, 500,000,000, 600,000,000, 700,000,000, 800,000,000,900,000,000, 1,000,000,000, 2,000,000,000, 3,000,000,000, 4,000,000,000,5,000,000,000, 6,000,000,000, 7,000,000,000, 8,000,000,000,9,000,000,000, and 10,000,000,000, tagged nucleic acid molecules on thehigh end of the range. In some embodiments, the population of taggednucleic acid molecules can include between 100,000,000, 200,000,000,300,000,000, 400,000,000, 500,000,000, 600,000,000, 700,000,000,800,000,000, 900,000,000, and 1,000,000,000 tagged nucleic acidmolecules on the low end of the range and 500,000,000, 600,000,000,700,000,000, 800,000,000, 900,000,000, 1,000,000,000, 2,000,000,000,3,000,000,000, 4,000,000,000, 5,000,000,000 tagged nucleic acidmolecules on the high end of the range.

In certain respects a percentage of the total sample nucleic acidmolecules in the population of sample nucleic acid molecules can betargeted to have MITs attached. In some embodiments, at least 1%, 2%,3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%,55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or99.9% of the sample nucleic acid molecules can be targeted to have MITsattached. In other respects a percentage of the sample nucleic acidmolecules in the population can have MITs successfully attached. In anyof the embodiments disclosed herein at least 1%, 2%, 3%, 4%, 5%, 6%, 7%,8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%,75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or 99.9% of the samplenucleic acid molecules can have MITs successfully attached to form thepopulation of tagged nucleic acid molecules. In any of the embodimentsdisclosed herein at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30,40, 50, 75, 100, 200, 300, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000,4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 15,000, 20,000,30,000, 40,000, or 50,000 of the sample nucleic acid molecules can haveMITs successfully attached to form the population of tagged nucleic acidmolecules.

In some embodiments disclosed herein, MITs can be oligonucleotidesequences of ribonucleotides or deoxyribonucleotides linked throughphosphodiester linkages. Nucleotides as disclosed herein can refer toboth ribonucleotides and deoxyribonucleotides and a skilled artisan willrecognize when either form is relevant for a particular application. Incertain embodiments, the nucleotides can be selected from the group ofnaturally-occurring nucleotides consisting of adenosine, cytidine,guanosine, uridine, 5-methyluridine, deoxyadenosine, deoxycytidine,deoxyguanosine, deoxythymidine, and deoxyuridine. In some embodiments,the MITs can be non-natural nucleotides. Non-natural nucleotides caninclude: sets of nucleotides that bind to each other, such as, forexample, d5SICS and dNaM; metal-coordinated bases such as, for example,2,6-bis(ethylthiomethyl)pyridine (SPy) with a silver ion and mondentatepyridine (Py) with a copper ion; universal bases that can pair with morethan one or any other base such as, for example, 2′-deoxyinosinederivatives, nitroazole analogues, and hydrophobic aromaticnon-hydrogen-bonding bases; and xDNA nucleobases with expanded bases. Incertain embodiments, the oligonucleotide sequences can be pre-determinedwhile in other embodiments, the oligonucleotide sequences can bedegenerate.

In some embodiments, MITs include phosphodiester linkages between thenatural sugars ribose and/or deoxyribose that are attached to thenucleobase. In some embodiments, non-natural linkages can be used. Theselinkages include, for example, phosphorothioate, boranophosphate,phosphonate, and triazole linkages. In some embodiments, combinations ofthe non-natural linkages and/or the phosphodiester linkages can be used.In some embodiments, peptide nucleic acids can be used wherein the sugarbackbone is instead made of repeating N-(2-aminoethyl)-glycine unitslinked by peptide bonds. In any of the embodiments disclosed hereinnon-natural sugars can be used in place of the ribose or deoxyribosesugar. For example, threose can be used to generateα-(L)-threofuranosyl-(3′-2′) nucleic acids (TNA). Other linkage typesand sugars will be apparent to a skilled artisan and can be used in anyof the embodiments disclosed herein.

In some embodiments, nucleotides with extra bonds between atoms of thesugar can be used. For example, bridged or locked nucleic acids can beused in the MITs. These nucleic acids include a bond between the2′-position and 4′-position of a ribose sugar.

In certain embodiments, the nucleotides incorporated into the sequenceof the MIT can be appended with reactive linkers. At a later time, thereactive linkers can be mixed with an appropriately-tagged molecule insuitable conditions for the reaction to occur. For example, aminoallylnucleotides can be appended that can react with molecules linked to areactive leaving group such as succinimidyl ester and thiol-containingnucleotides can be appended that can react with molecules linked to areactive leaving group such as maleimide. In other embodiments,biotin-linked nucleotides can be used in the sequence of the MIT thatcan bind streptavidin-tagged molecules.

Various combinations of the natural nucleotides, non-naturalnucleotides, phosphodiester linkages, non-natural linkages, naturalsugars, non-natural sugars, peptide nucleic acids, bridged nucleicacids, locked nucleic acids, and nucleotides with appended reactivelinkers will be recognized by a skilled artisan and can be used to formMITs in any of the embodiments disclosed herein.

Amplifying Tagged Nucleic Acid Molecules

In some embodiments, methods of the present disclosure includeamplifying the tagged nucleic acid molecules before determining thesequences of the tagged nucleic acid molecules. Typically, multiplerounds of amplification occur during sample preparation forhigh-throughput sequencing, as is known in the art. These amplificationsteps generally all occur after the MITs have been attached to thenucleic acid molecules, although amplification of the sample nucleicacid molecules can occur before MIT attachment in some embodiments. Incertain embodiments, after MITs are attached to sample nucleic acidsegments of sample nucleic acid molecules, at least 1, 2, 3, 4, 5, or 6amplification reactions are performed. In high-throughput sequencing,for example, amplification reactions can include amplifying the initialnucleic acid in the sample to generate the library to be sequenced,clonally amplifying the library, typically onto a solid support, andadditional amplification reactions to add additional information orfunctionality such as sample identifying barcodes. Barcodes can be addedat any time during the amplification process and before and/or aftertarget enrichment as discussed below. The tagged sample nucleic acidmolecules can have one or more than one barcode on one or both ends.Each amplification reaction typically includes multiple cycles (e.g. 2,3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 onthe low end of the range of number of cycles and 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 75, or 100cycles on the high end of the range) of amplification either throughtemperature cycling or natural biochemical reaction cycling as occursduring isothermal amplification. A method of any of the embodimentsprovided herein, in some examples, can include an amplification stepwhere at least 10, 15, 20, 25, or 30 cycles (e.g. thermocycles in a PCRamplification) of amplification are performed.

In some embodiments, after attaching the MITs, the tagged nucleic acidmolecules can be amplified using universal primers that bind topreviously attached universal amplification primer binding sequences togenerate a library of sample nucleic acid molecules. Specific targetnucleic acids in the library of nucleic acid molecules can be enrichedfor example through multiplex PCR, especially one-sided PCR, or throughhybrid capture. The enrichment step can be followed by another universalamplification reaction. Regardless of whether there is a targetedamplification step, an optional barcoding amplification reaction can beused to barcode the tagged nucleic acid molecules that arose from samplenucleic acid molecules from separate samples or subpools such that theproducts from multiple reaction mixtures or subpools can be pooled. Asis known, such barcodes can make it possible to identify the sample fromwhich a tagged nucleic acid molecule was generated. This can be used toidentify multiple starting samples and it can be useful if the samplenucleic acid molecules are split after labeling to increase the totalnumber of tag combinations. Such barcodes differ from MITs of thepresent disclosure because they do not identify individual samplenucleic acid molecules but rather they identify samples from whichnucleic acid molecules arose in a mixture of samples. The tagged nucleicacid molecules or amplified tagged nucleic acid molecules are typicallytemplated onto one or more solid supports and clonally amplified orclonal amplification can occur during the templating amplificationreaction. It is noteworthy that amplification errors can be introducedat any amplification step in the process. Using the methods disclosedherein, it is possible to identify at which amplification step an erroroccurs, or if the error occurs during a subsequent sequencing reaction.For example, if a sample is split into multiple PCRs, and each PCR addsa new, different MIT, it is possible to determine if an error occurredin a particular PCR step.

In some embodiments, the sample nucleic acid molecules are unalteredbefore the MITs are attached; after the MITs are attached the taggednucleic acid molecules are amplified using universal primers to producea library or population of tagged nucleic acid molecules; the library ofamplified tagged nucleic acid molecules undergo target enrichmentthrough multiplex PCR (e.g. one-sided multiplex PCR); the enrichedtagged nucleic acid molecules undergo an optional barcodingamplification step; clonal amplification onto one or more solid supportsis performed; the sequences of the tagged nucleic acid molecules aredetermined; and the sample nucleic acid molecules are identified usingthe determined sequences of the attached MITs.

In any of the embodiments disclosed herein, these amplification stepscan be performed using well-known methods in the art, such as PCRamplification with thermocycling or isothermal amplification such asrecombinase polymerase amplification. In any of the amplification stepsdisclosed herein, a skilled artisan will understand how to adapt themethods for isothermal amplification.

In some embodiments, the tagged nucleic acid molecules can be used togenerate a library for sequencing, especially high-throughputsequencing. Typically, the tagged nucleic acid molecules are amplifiedusing universal primers that bind universal primer binding sequencesthat have been incorporated into the tagged nucleic acid molecules asdiscussed elsewhere herein. In some embodiments, universal amplificationcan be performed for a number of cycles, such as between 1, 2, 3, 4, 5,6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20 cycles on thelow end of the range and 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, and 50cycles on the high end of the range. In some embodiments, amplificationcan be performed such that each of the tagged nucleic acid molecules iscopied to generate between 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30,40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400, 500, 600, 700,800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000,10,000, 15,000, 20,000, 30,000, 40,000, 50,000, 100,000, 200,000,300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000,1,000,000, 1,250,000, 1,500,000, 2,000,000, 2,500,000, 3,000,000,4,000,000, 5,000,000, 10,000,000, 20,000,000, 30,000,000, 40,00,000, and50,000,000 copies on the low end and 5, 6, 7, 8, 9, 10, 15, 20, 25, 30,40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400, 500, 600, 700,800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000,10,000, 15,000, 20,000, 30,000, 40,000, 50,000, 100,000, 200,000,300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000,1,000,000, 1,250,000, 1,500,000, 2,000,000, 2,500,000, 3,000,000,4,000,000, 5,000,000, 6,000,000, 7,000,000, 8,000,000, 9,000,000,10,000,000, 20,000,000, 30,000,000, 40,00,000, 50,000,000, 100,000,000,200,000,000, 300,000,000, 400,000,000, 500,000,000, 600,000,000,700,000,000, 800,000,000, 900,000,000, and 1,000,000,000 copies on thehigh end.

Target Enrichment

Methods of the present disclosure, in certain embodiments, can include atarget enrichment step before the step of determining the sequence ofthe sample nucleic acid molecules. In some embodiments, targetenrichment is performed using a multiplex PCR reaction, especially aone-sided PCR reaction. In these embodiments, a universal primer and aplurality of target-specific primers that bind to internal sequences oftarget sample nucleic acid segments are used such that they generateamplicons from tagged nucleic acid molecules with both a universalprimer binding sequence and a target-specific binding sequence but noamplicons are generated from tagged nucleic acid molecules lackingeither or both of these sequences. In some embodiments, the universalprimer can bind to the 5′ universal primer binding site of one strand ofDNA and the target-specific primers can bind to the complement of theDNA strand within the nucleic acid segment 3′ to the universal primerbinding site on the other strand of complementary DNA. The bindingorientation can be reversed and the universal primer can bind to the 3′universal primer binding site of one strand and the target-specificprimers can bind to the complement of the DNA strand within the nucleicacid segment 5′ to the universal primer binding site on the other strandof complementary DNA.

In some embodiments, of the present disclosure, preferentially enrichingthe DNA includes obtaining a plurality of hybrid capture probes thattarget the desired sequences, hybridizing the hybrid capture probes tothe DNA in the sample and physically removing some or all of theunhybridized DNA from the sample of DNA. Thus, sequences complementaryto the target tagged nucleic acid molecules are bound to solid supportsand the tagged nucleic acid molecules are added under conditions suchthat the targeted tagged nucleic acid molecules anneal to thecomplementary sequence and the untargeted tagged nucleic acid moleculesdo not. After removing untargeted tagged nucleic acid molecules, thereaction conditions can be adjusted such that the target tagged nucleicacid molecules dissociate from the solid support and can be isolated. Insome embodiments, an amplification step can be performed after hybridcapture using universal amplification primers.

Hybrid capture probe refers to any nucleic acid sequence, possiblymodified, that is generated by various methods such as PCR or directsynthesis and intended to be complementary to one strand of a specifictarget DNA sequence in a sample. The exogenous hybrid capture probes maybe added to a prepared sample and hybridized through adenature-reannealing process to form duplexes of exogenous-endogenousfragments. These duplexes may then be physically separated from thesample by various means. Hybrid capture probes were originally developedto target and enrich large fractions of the genome with relativeuniformity between targets. In that application, it was important thatall targets be amplified with enough uniformity that all target locicould be detected by sequencing; however, no regard was paid toretaining the proportion of alleles in original sample. Followingcapture, the alleles present in the sample can be determined by directsequencing of the captured molecules. These sequencing reads can beanalyzed and counted according the allele type.

As discussed herein, methods of the present disclosure in someembodiments, include one-sided multiplex PCR methods. In such methods,tagged nucleic acid molecules that have an adapter or adapters at theend or ends can be used. One-sided PCR can be performed in two steps.For example, a first one-sided PCR can be performed on targeted taggednucleic acid molecules with a plurality of forward primers specific foreach targeted tagged nucleic acid molecule and a reverse primer thatbinds a universal primer binding site that is present on the ligationadapters on all the tagged nucleic acid molecules. A second one-sidedPCR can then be performed on the products of the first one-sided PCRusing a plurality of forward primer specific for each targeted taggednucleic acid molecule and a reverse primer that binds the same or adifferent universal primer binding site from the universal primerbinding site used in the first one-sided PCR reaction.

In some embodiments, the tagged nucleic acid molecules undergotemplating through clonal amplification onto one or more solid supports,either in one or two reactions. Methods are well-known in the art fortemplating and/or performing clonal amplification and depend on thesequencing method used for analysis. A skilled artisan will recognizethe methods to use to perform clonal amplification.

Amplification Reaction Mixtures

In some embodiments, amplifying the nucleic acid molecules can includeforming an amplification reaction mixture. An amplification reactionmixture useful for the present disclosure can include componentswell-known in the art, especially for PCR amplification. For example,the reaction mixture typically includes a source of nucleotides such asnucleotide triphosphates, a polymerase, magnesium, and primers, andoptionally one or more tagged nucleic acid molecules. The reactionmixture in certain embodiments, is formed by combining a polymerase,nucleotide triphosphates, tagged nucleic acid molecules, and a set offorward and/or reverse primers. Accordingly, in certain embodimentsprovided herein is a reaction mixture that includes a population oftagged nucleic acid molecules and a pool of primers, at least some ofwhich bind the tagged nucleic acid molecules within the population oftagged nucleic acid molecules. In addition to the MIT sequences, thetagged nucleic acid molecules can include adapter sequences, forexample, for binding primers for sequencing reactions and/or universalamplification reactions. In some embodiments, the forward and reverseprimers for amplifying tagged nucleic acid sequences can be designed tobind to universal primer binding sequences that have been attached tothe tagged nucleic acid molecules such that all tagged nucleic acidsequences are amplified. In some embodiments, the forward and reverseprimers can be designed such that one binds to a universal primerbinding sequence and the other binds to target-specific sequences withinthe sample nucleic acid segments, such as in one-sided PCR. In otherembodiments, the forward and reverse primers can both be designed tobind to target-specific sequences within the sequences of the samplenucleic acid segments, such as in two-sided PCR.

In any of the embodiments disclosed herein, the reaction mixture caninclude between 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90,95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 225, 250,300, 350, 400, 450, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000,5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 15,000, 20,000, 30,000,40,000, 50,000, 100,000, 200,000, 300,000, 400,000, 500,000, 600,000,700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 2,000,000,2,500,000, 3,000,000, 4,000,000, 5,000,000, 10,000,000, 20,000,000,30,000,000, 40,00,000, 50,000,000, 100,000,000, 200,000,000,300,000,000, 400,000,000, 500,000,000, 600,000,000, 700,000,000,800,000,000, 900,000,000, and 1,000,000,000 tagged nucleic acidmolecules on the low end of the range and 3, 4, 5, 6, 7, 8, 9, 10, 15,20, 25, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400, 500,600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000,8,000, 9,000, 10,000, 15,000, 20,000, 30,000, 40,000, 50,000, 100,000,200,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000,1,000,000, 1,250,000, 1,500,000, 2,000,000, 2,500,000, 3,000,000,4,000,000, 5,000,000, 6,000,000, 7,000,000, 8,000,000, 9,000,000,10,000,000, 20,000,000, 30,000,000, 40,00,000, 50,000,000, 100,000,000,200,000,000, 300,000,000, 400,000,000, 500,000,000, 600,000,000,700,000,000, 800,000,000, 900,000,000, 1,000,000,000, 2,000,000,000,3,000,000,000, 4,000,000,000, 5,000,000,000, 6,000,000,000,7,000,000,000, 8,000,000,000, 9,000,000,000, and 10,000,000,000 taggednucleic acid molecules on the high end of the range. In someembodiments, the reaction mixture can include between 1, 2, 3, 4, 5, 6,7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 150,200, 250, 300, 400, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000,5,000, 6,000, 7,000, 8,000, 9,000, and 10,000 copies of each of thetagged nucleic acid molecules on the low end of the range and 20, 25,30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400, 500,600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000,8,000, 9,000, 10,000, 20,000, 30,000, 40,000, 50,000, and 100,000 copiesof each of the tagged nucleic acid molecules on the high end of therange.

In any of the embodiments disclosed herein, at least 10%, 15%, 20%, 25%,30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%,96%, 97%, 98%, 99%, or 99.9% of the tagged nucleic acid molecules can besuccessfully amplified, wherein successful amplification is defined asPCR that has an efficiency of at least 80%, 85%, 90%, 95%, 96%, 97%,98%, 99%, 99.9%, or 100%.

In further embodiments, the reaction mixture can include a population ofbetween 100 and 1,000,000 tagged nucleic acid molecules, each between 50and 500 nucleotides in length, with between 10 and 100,000 differentsample nucleic acid segments, and a set of MITs of between 10 and 500MITs that are each between 4 and 20 nucleotides in length, wherein theratio of the number of sample nucleic acid segments to the number ofMITs in the population is between 2:1 and 100:1. In certain embodiments,each member of the set of MITs is attached to at least one taggednucleic acid molecule of the population. In certain embodiments, atleast two tagged nucleic acid molecules of the population include atleast one identical MIT and a sample nucleic acid segment that isgreater than 50% different. In some embodiments, the reaction mixturecan include a polymerase or ligase.

In some embodiments, the reaction mixture can include a set, library,plurality, or pool of primers, that includes 25, 50, 100, 200, 250, 300,400, 500, 1,000, 2,500, 5,000, 10,000, 20,000, 25,000, or 50,000 primersor primer pairs on the low end of the range, and 200, 250, 300, 400,500, 1,000, 2,500, 5,000, 10,000, 20,000, 25,000, 50,000, 60,000,70,000, 80,000, 90,000, 100,000, 125,000, 150,000, 200,000, 250,000,300,000, 400,000, or 500,000 primers or primer pairs on the high end ofthe range, that each bind to a primer binding sequence located withinone or more of a plurality of the tagged nucleic acid molecules.

In some embodiments, a library of nucleic acid molecules is formed thatis useful for sequencing. In some embodiments, the library can includebetween 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 150,200, 250, 300, 400, 500, 600, 700, 800, 900, and 1,000 copies of each ofthe tagged nucleic acid molecules on the low end of the range and 20,25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400,500, 600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000,7,000, 8,000, 9,000, and 10,000 copies of each of the tagged nucleicacid molecules on the high end of the range.

In some embodiments, the library of nucleic acid molecules can includeat least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60,70, 80, 90, 100, 150, 200, 250, 300, 400, 500, 600, 700, 800, 900, and1,000 tagged nucleic acid molecules with an identical attached first MITat the 5′ end of nucleic acid segment, an identical attached second MITat the 3′ end of nucleic acid segment, and a sample nucleic acid segmentthat has at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19, or 20 nucleotide differences.

In some embodiments, the library of nucleic acid molecules can include aplurality of clonal population of each of the tagged nucleic acidmolecules on a solid support or plurality of solid supports.

In some embodiments, a polymerase with proof-reading activity, apolymerase without (or with negligible) proof-reading activity, or amixture of a polymerase with proof-reading activity and a polymerasewithout (or with negligible) proof-reading activity is included inamplification reaction mixtures herein. In some embodiments, a hot startpolymerase, a non-hot start polymerase, or a mixture of a hot startpolymerase and a non-hot start polymerase is used. In some embodiments,a HotStarTaq DNA polymerase is used (see, for example, Qiagen, Hilden,Germany). In some embodiments, AmpliTaq Gold® DNA Polymerase is used(Thermo Fisher, Carlsbad, Calif.). In some embodiments, a PrimeSTAR GXLDNA polymerase, a high-fidelity polymerase that provides efficient PCRamplification when there is excess template in the reaction mixture, andwhen amplifying long products, is used (Takara Clontech, Mountain View,Calif.). In some embodiments, KAPA Taq DNA Polymerase or KAPA TaqHotStart DNA Polymerase are used; they are based on the single-subunit,wild-type Taq DNA polymerase of the thermophilic bacterium Thermusaquaticus and have 5′-3′ polymerase and 5′-3′ exonuclease activities,but no 3′ to 5′ exonuclease (proofreading) activity (Kapa Biosystems,Wilmington, Mass.). In some embodiments, Pfu DNA polymerase is used; itis a highly thermostable DNA polymerase from the hyperthermophilicarchaeum Pyrococcus furiosus. Pfu catalyzes the template-dependentpolymerization of nucleotides into duplex DNA in the 5′→3′ direction andalso exhibits 3′→5′ exonuclease (proofreading) activity that enables thepolymerase to correct nucleotide incorporation errors. It has no 5′→3′exonuclease activity (Thermo Fisher Scientific, Waltham, Mass.). In someembodiments, Klentaq1 is used; it is a Klenow-fragment analog of Taq DNApolymerase with no exonuclease or endonuclease activity (DNA PolymeraseTechnology, St. Louis, Mo.). In some embodiments, the polymerase is aPhusion DNA polymerase, such as Phusion High-Fidelity DNA polymerase orPhusion Hot Start Flex DNA polymerase (New England BioLabs, Ipswich,Mass.). In some embodiments, the polymerase is a Q5® DNA Polymerase,such as Q5® High-Fidelity DNA Polymerase or Q5® Hot Start High-FidelityDNA Polymerase (New England BioLabs). In some embodiments, thepolymerase is a T4 DNA polymerase (New England BioLabs).

In some embodiments, between 5 and 600 Units/mL (Units per 1 mL ofreaction volume) of polymerase is used, such as between 5 to 100, 100 to200, 200 to 300, 300 to 400, 400 to 500, or 500 to 600 Units/mL,inclusive.

PCR Methods

In some embodiments, hot-start PCR is used to reduce or preventpolymerization prior to PCR thermocycling. Exemplary hot-start PCRmethods include initial inhibition of the DNA polymerase or physicalseparation of reaction components reaction until the reaction mixturereaches the higher temperatures. In some embodiments, the slow releaseof magnesium is used. DNA polymerase requires magnesium ions foractivity, so the magnesium is chemically separated from the reaction bybinding to a chemical compound, and is released into the solution onlyat high temperature. In some embodiments, non-covalent binding of aninhibitor is used. In this method, a peptide, antibody, or aptamer canbe non-covalently bound to the enzyme at low temperature to inhibit itsactivity. After incubation at elevated temperature, the inhibitor isreleased and the reaction starts. In some embodiments, a cold-sensitiveTaq polymerase is used, such as a modified DNA polymerase with almost noactivity at low temperature. In some embodiments, chemical modificationis used. In this method, a molecule is covalently bound to the sidechain of an amino acid in the active site of the DNA polymerase. Themolecule is released from the enzyme by incubation of the reactionmixture at elevated temperature. Once the molecule is released, theenzyme is activated.

In some embodiments, the amount of template nucleic acids (such as anRNA or DNA sample) is between 20 and 5,000 ng, such as between 20 to200; 200 to 400; 400 to 600; 600 to 1,000; 1,000 to 1,500; or 2,000 to3,000 ng, inclusive.

Methods for performing PCR are well-known in the art. Such methodstypically include cycles of a denaturing step, an annealing step, and anelongation step, which can be the same or different than the annealingstep.

An exemplary set of conditions includes a semi-nested PCR approach. Thefirst PCR reaction uses 20 μl a reaction volume with 2× Qiagen MM finalconcentration, 1.875 nM of each primer in the library (outer forward andreverse primers), and DNA template. Thermocycling parameters include 95°C. for 10 minutes; 25 cycles of 96° C. for 30 seconds, 65° C. for 1minute, 58° C. for 6 minutes, 60° C. for 8 minutes, 65° C. for 4minutes, and 72° C. for 30 seconds; and then 72° C. for 2 minutes, andthen a 4° C. hold. Next, 2 μl of the resulting product, diluted 1:200,is used as input in a second PCR reaction. This reaction uses a 10 μlreaction volume with 1× Qiagen MM final concentration, 20 nM of eachinner forward primer, and 1 μM of reverse primer tag. Thermocyclingparameters include 95° C. for 10 minutes; 15 cycles of 95° C. for 30seconds, 65° C. for 1 minute, 60° C. for 5 minutes, 65° C. for 5minutes, and 72° C. for 30 seconds; and then 72° C. for 2 minutes, andthen a 4° C. hold. The annealing temperature can optionally be higherthan the melting temperatures of some or all of the primers, asdiscussed herein (see U.S. patent application Ser. No. 14/918,544, filedOct. 20, 2015, which is herein incorporated by reference in itsentirety).

The melting temperature (T_(m)) is the temperature at which one-half(50%) of a DNA duplex of an oligonucleotide (such as a primer) and itsperfect complement dissociates and becomes single strand DNA. Theannealing temperature (T_(A)) is the temperature one runs the PCRprotocol at. For prior methods, it is usually 5° C. below the lowestT_(m) of the primers used, thus close to all possible duplexes areformed (such that essentially all the primer molecules bind the templatenucleic acid). While this is highly efficient, at lower temperaturesunspecific reactions are more likely to occur. One consequence of havingtoo low a T_(A) is that primers may anneal to sequences other than thetrue target, as internal single-base mismatches or partial annealing maybe tolerated. In some embodiments, of the present disclosures, the T_(A)is higher than (T_(m)), where at a given moment only a small fraction ofthe targets has a primer annealed (such as only ˜1-5%). If these getextended, they are removed from the equilibrium of annealing anddissociating primers and target (as extension increases T_(m) quickly toabove 70° C.), and a new ˜1-5% of targets has primers. Thus, by givingthe reaction a long time for annealing, one can get ˜100% of the targetscopied per cycle.

In various embodiments, the range of the annealing temperature isbetween 1° C., 2° C., 3° C., 4° C., 5° C., 6° C., 7° C., 8° C., 9° C.,10° C., 11° C., 12° C., and 13° C. on the low end of the range and 2°C., 3° C., 4° C., 5° C., 6° C., 7° C., 8° C., 9° C., 10° C., 11° C., 12°C., 13° C., and 15° C. on the high end of the range, greater than themelting temperature (such as the empirically measured or calculatedT_(m)) of at least 25, 50, 60, 70, 75, 80, 90, 95, or 100% of thenon-identical primers. In various embodiments, the annealing temperatureis between 1° C. and 15° C. (such as between 1° C. to 10° C., 1° C. to5° C., 1° C. to 3° C., 3° C. to 5° C., 5° C. to 10° C., 5° C. to 8° C.,8° C. to 10° C., 10° C. to 12° C., or 12° C. to 15° C., inclusive)greater than the melting temperature (such as the empirically measuredor calculated T_(m)) of at least 25; 50; 75; 100; 300; 500; 750; 1,000;2,000; 5,000; 7,500; 10,000; 15,000; 19,000; 20,000; 25,000; 27,000;28,000; 30,000; 40,000; 50,000; 75,000; 100,000; or all of thenon-identical primers. In various embodiments, the annealing temperatureis between 1 and 15° C. (such as between 1° C. to 10° C., 1° C. to 5°C., 1° C. to 3° C., 3° C. to 5° C., 3° C. to 8° C., 5° C. to 10° C., 5°C. to 8° C., 8° C. to 10° C., 10° C. to 12° C., or 12° C. to 15° C.,inclusive) greater than the melting temperature (such as the empiricallymeasured or calculated T_(m)) of at least 25%, 50%, 60%, 70%, 75%, 80%,90%, 95%, or all of the non-identical primers, and the length of theannealing step (per PCR cycle) is between 5 and 180 minutes, such as 15and 120 minutes, 15 and 60 minutes, 15 and 45 minutes, or 20 and 60minutes, inclusive.

In addition to thermocycling during PCR, isothermal amplification hasbeen recognized as a means to amplify nucleic acid molecules. In any ofthe PCR methods disclosed herein, a skilled artisan will understand howto adapt the methods for use with this technology. For example, in someembodiments, the reaction mixture can include tagged nucleic acidmolecules, a pool of primers, nucleotide triphosphates, magnesium, andan isothermal polymerase. There are several isothermal polymerasesavailable to perform isothermal amplification. These include Bst DNApolymerase, full length; Bst DNA polymerase, large fragment; Bst 2.0 DNApolymerase; Bst 2.0 WarmStart DNA polymerase; and Bst 3.0 DNA polymerase(all available from New England Biolabs). The polymerase used can bedependent on the method of isothermal amplification. There are severaltypes of isothermal amplification available, including recombinasepolymerase amplification (RPA), loop-mediated isothermal amplification(LAMP), strand displacement amplification (SDA), helicase-dependentamplification (HDA), nicking enzyme amplification reaction (NEAR), andtemplate walking.

Determining the Sequences of Tagged Nucleic Acid Molecules

In some embodiments, the sequences of tagged nucleic acid molecules aredetermined directly by methods known in the art, especiallyhigh-throughput sequencing. More typically, the sequences of taggednucleic acid molecules are determined after one or more rounds ofamplification that occurs during sample preparation for high-throughputsequencing. Such amplifications typically include library preparation,clonal amplification, and amplification(s) to add additional sequencesor functionality, such as sample barcodes, to the sample nucleic acidmolecules. During high-throughput sequencing sample preparation, taggednucleic acid molecules are typically clonally amplified onto one or moresolid supports. These monoclonal or substantially monoclonal coloniesare then subjected to a sequencing reaction. Furthermore, nextgeneration sequencing sample preparation can include a targetedamplification reaction typically after library preparation and beforeclonal amplification. Such targeted amplification can be a multiplexamplification reaction.

In any of the embodiments disclosed herein, the methods and compositionscan be used to identify amplification errors versus true sequencevariants in the sample nucleic acid molecules. The present disclosurecan further identify the likely source of amplification error and canfurther identify the most likely true sequence of the initial samplenucleic acid molecule.

In some embodiments, of the method provided herein, at least a portionand in some embodiments, the entire sequence of at least one taggednucleic acid molecule is determined. Methods for determining thesequence of a nucleic acid molecule are known in the art. Any of thesequencing methods known in the art, for example Sanger sequencing,pyrosequencing, reversible dye terminator sequencing, sequencing byligation, or sequencing by hybridization, can be used for such sequencedetermination. In some embodiments, high-throughput next-generation(massively parallel) sequencing techniques such as, but not limited to,those employed in Solexa (I lumina), Genome Analyzer IIx (Illumina),MiSeq (Illumina), HiSeq (Illumina), 454 (Roche), SOLiD (LifeTechnologies), Ion Torrent (Life Technologies, Carlsbad, Calif.), GSFLX+ (Roche), True Single Molecule Sequencing platform (Helicos),electron microscope sequencing method (Halcyon Molecular) can be used,or any other sequencing method can be used for sequencing the taggednucleic acid molecules generated by the methods provided herein. In someembodiments, any high-throughput, massively-parallel sequencing methodcan be used and a skilled artisan will understand how to adjust thedisclosed methods to accomplish the appropriate MIT attachment. Thus, asequencing by synthesis or sequencing by ligation, high-throughputreaction can be used, for example. Furthermore, the sequencer can detecta signal generated during the sequencing reaction, which can be afluorescent signal or an ion, such as a hydrogen ion. All of thesemethods physically transform the genetic data stored in a sample of DNAinto a set of genetic data that is typically stored in a memory devicein route to being processed.

Identifying the Sample Nucleic Acid Molecules

The step of determining the sequences of the tagged nucleic acidmolecules includes determining the sequences of at least a portion ofthe sample nucleic acid molecules, sample nucleic acid segments, ortarget loci and the sequences of tags that remain attached to the samplenucleic acid segments, including the sequences of MITs. In someembodiments, copies of tagged nucleic acid molecules that have beenderived from the same initial tagged nucleic acid molecule can beidentified by comparing the MIT sequences attached to the tagged nucleicacid molecule. Copies derived from the same initial tagged nucleic acidmolecules will have the same MITs attached in the same location relativeto the sample nucleic acid segment. In some embodiments, thefragment-specific insert ends are mapped to specific locations in thegenome of the organism and these mapped locations or the sequences ofthe fragment-specific insert ends themselves as discussed herein areused in conjunction with the sequences of the MITs to identify theinitial tagged nucleic acid molecules from which the copies are derived.In some embodiments, tagged nucleic acid molecules comprisingcomplementary MITs and complementary nucleic acid segment sequences,i.e. tagged nucleic acid molecules that have been derived from the samenucleic acid molecule and represent the plus and minus strands of thesample nucleic acid molecule, are identified and paired. In someembodiments, the paired MIT families are used to verify differences inthe original sequence. Any change in the sequence should be present inall copies of the tagged nucleic acid molecules derived from the samplenucleic acid molecules. This information provides additional confidencethat the sequences of the tagged nucleic acid molecules derived from theplus strand and the minus strand of the sample represent a difference inthe sequence of the sample nucleic acid molecule and not a changeintroduced during sample preparation or an error in base-calling duringsequencing.

In some embodiments, two main types of tagged nucleic acid molecules aregenerated that will be informative for further analysis: tagged nucleicacid molecules with identical attached MITs in the same positions andwith substantially the same sample nucleic acid segment sequences andtagged nucleic acid molecules with different attached MITs and withsubstantially the same sample nucleic acid segment sequences. Asdiscussed in detail herein, the tagged nucleic acid molecules withidentical attached MITs in the same positions and with substantially thesame sample nucleic acid segment sequences can be used to identifyamplification errors and the tagged nucleic acid molecules with at leastone difference between the attached MITs, and with substantially thesame sample nucleic acid segment sequences can be used to identify truesequence variants.

After the MITs are attached, amplification errors can be identified bycomparing the sequences of tagged nucleic acid molecules with identicalMITs in the same relative positions and with substantially the samesample nucleic acid sequences. When both strands of an initial samplenucleic acid molecule are tagged with the same MIT or MITs, it ispossible to identify paired MIT nucleic acid segment families that havecomplementary MIT and nucleic acid segment sequences. These paired MITnucleic acid segment families can be used to boost the confidence thatthe sequence variation was present on both strands of the sample nucleicacid molecule. If the tagged nucleic acid molecules derived from thesample nucleic acid molecule show differences in their sequences, theneither there was a mismatch present in the sample nucleic acid moleculeor an error was introduced during amplification or base calling. Thesequences from a paired MIT nucleic acid segment family with sequencedifferences will typically be discarded before further analysis isperformed. However, these paired MIT nucleic acid segment families withsequence differences could be used to identify mismatches in the samplenucleic acid molecules.

Amplification errors that introduce one or more changes into thesequence of a nucleic acid segment will not be present in all copiesderived from the initial tagged nucleic acid molecule. At most 25% ofthe copies derived from both strands of an initial tagged nucleic acidmolecule will have the error in the sequence of the nucleic acid segmentif the error is introduced during the first round of amplification. Ifamplification proceeds with perfect efficiency, the percentage of copieswith a specific error will be halved during every round ofamplification, i.e. 12.5% of the copies derived from the initial taggednucleic acid molecule will have the error if it is introduced during thesecond round of amplification and 6.25% of the copies derived from theinitial tagged nucleic acid molecule will have the error if it isintroduced during the third round of amplification, etc. Using thisknowledge, it can be possible to identify or estimate when anamplification error was introduced; including, in the embodiments wheremultiple amplifications occur after the MITs are attached, at which stepthe amplification error was introduced. In any of the embodimentsdisclosed herein, when amplification errors are present within thesample nucleic acid segment, the methods detailed herein can be used todetermine the most likely sequence of the initial sample nucleic acidmolecule. For example, the most likely sequence can be determined fromthe pool of copies of an initial tagged nucleic acid molecule as themost common sequence. In some embodiments, prior probabilities can beused when determining the most likely sequence, for example, knownmutation rates at specific chromosomal sites in normal or diseased cellsor the population frequency of specific single nucleotide polymorphisms.

The probability of having an identical amplification error in more thanone tagged nucleic acid molecule with different MITs and substantiallythe same nucleic acid segment sequence is exceedingly low, such thatidentical sequence variants on tagged nucleic acid molecules withsubstantially the same sequences and identical MITs in the same relativepositions are considered to be derived from the same molecule and nothaving arisen independently.

True sequence variations present in the sample nucleic acid segments canbe identified since all copies derived from one initial tagged nucleicacid molecule will have the same sequence in the variant location and atleast one pool of copies of a tagged nucleic acid molecule withsubstantially the same sample nucleic acid segment sequence anddifferences in the MITs will have a different sequence in the samevariant location, wherein differences in the MITs can be either at leastone different attached MIT from the set of MITs or different relativepositions of identical MITs.

In any of the embodiments disclosed herein, a sequence difference can becalled as an amplification error if the percentage of the copies derivedfrom the same initial tagged nucleic acid molecule with the sequencechange is below 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10% 9%, 8%, 7%,6%, 5%, 4%, 3%, 2%, or 1%. In certain embodiments, copies can be said tobe derived from the same initial tagged nucleic acid molecule if theattached MITs are identical and in the same relative location and if thesample nucleic acid segment sequence is substantially the same. In anyof the embodiments disclosed herein, a sequence change can be called asa true sequence variant in the initial tagged nucleic acid molecule ifthe sequence differs in at least two tagged nucleic acid molecules withsubstantially the same sample nucleic acid segments and the pools of thecopies derived from each of the at least two tagged nucleic acidmolecules with substantially the same sample nucleic acid segments areat least 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, 99.9% or 100%identical within each pool, and each pool is identified by having atleast one different MIT and/or an MIT at a different location relativeto a sample nucleic acid segment.

In some embodiments, the sequences of the tagged nucleic acid moleculescan be used to identify between 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%,30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%,96%, 97%, 98%, 99%, or 99.9% of the sample nucleic acid molecules on thelow end of the range or 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35%,40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%,98%, 99%, 99.9%, or 100% of the sample nucleic acid molecules on thehigh end of the range.

In some embodiments, for each sample nucleic acid molecule the methodscan be used to identify between 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20,25, 50, 75, 100, 250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000,15,000, 20,000, 25,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000,90,000, and 100,000 amplification errors on the low end of the range and5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75,100, 250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 15,000,20,000, 25,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000, 90,000,100,000, 200,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000,900,000, and 1,000,000 amplification errors on the high end of therange. In some embodiments, for each sample nucleic acid molecule themethods can be used to identify between 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75, 100, 250, 500,1,000, 2,000, 3,000, 4,000, 5,000, 10,000, 15,000, 20,000, 25,000,30,000, 40,000, 50,000, 60,000, 70,000, 80,000, 90,000, and 100,000 truesequence variants in the sample nucleic acid molecule on the low end ofthe range and 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,18, 19, 20, 25, 30, 35, 40, 45, 50, 75, 100, 250, 500, 1,000, 2,000,3,000, 4,000, 5,000, 10,000, 15,000, 20,000, 25,000, 30,000, 40,000,50,000, 60,000, 70,000, 80,000, 90,000, 100,000, 200,000, 300,000,400,000, 500,000, 600,000, 700,000, 800,000, 900,000, and 1,000,000 truesequence variants in the sample nucleic acid molecule on the high end ofthe range.

Other uses for the embodiments disclosed herein will be apparent to askilled artisan who will understand how to adapt the methods. Forexample, the methods can be used to measure amplification bias,especially changes in the amplification bias of specific nucleic acidmolecules after the introduction of amplification errors. The methodscan also be used to characterize the mutation rates of polymerases. Bysplitting the samples and barcoding the reaction mixtures, it ispossible to characterize the mutation rates of different polymerases atthe same time.

Kits for MITs

Any of the components used in the various embodiments disclosed hereincan be assembled into kits. A kit can include a container that holds anyof the sets of MITs disclosed herein. The MITs can be between 2, 3, 4,5, 6, 7, 8, 9, 10, 11, 12, 13, 14, and 15 nucleotides long on the lowend of the range and 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,19, 20, 25, and 30 nucleotides long on the high end of the range. TheMITs can be double-strand nucleic acid adaptors. These adaptors canfurther comprise a portion of a Y-adaptor nucleic acid molecule with abase-paired double-stranded polynucleotide segment and at least onenon-base-paired single-stranded polynucleotide segment. These Y-adaptorscan comprise identical sequences besides the sequences of the MITs. Thedouble-stranded polynucleotide segment of the Y-adaptors can be between1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, and 25 nucleotides long on thelow end of the range and 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70,80, 90, and 100 nucleotides long on the high end of the range. Thesingle-stranded polynucleotide segment of the Y-adaptors can be between1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, and 25 nucleotides long on thelow end of the range and 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70,80, 90, and 100 nucleotides long on the high end of the range.

In any of the embodiments disclosed herein, the MITs can be a part of apolynucleotide segment that includes a universal primer bindingsequence. In some embodiments, the MITs can be located 5′ to theuniversal primer binding sequences. In some embodiments, the MITs can belocated within the universal primer binding sequence such that when thepolynucleotide segment is bound to DNA, the sequences of the MITs willform non-base-paired loops. In any of the embodiments disclosed herein,the kit can include a set of sample-specific primers designed to bind tointernal sequences of the sample nucleic acid molecules, nucleic acidsegments, or target loci. In some embodiments, the MITs can be a portionof a polynucleotide that further comprises the sample-specific primersequences. In these embodiments the MIT can be located 5′ to thesample-specific primer sequences or the MITs can be located within thesample-specific primer sequences such that when the polynucleotidesegment is bound to DNA, the sequences of the MITs will formnon-base-paired loops. In some embodiments, the set of sample-specificprimers can include forward and reverse primers for each target locus.In some embodiments, the set of sample-specific primers can be forwardor reverse primers and a set of universal primers can be used as thereverse or forward primers, respectively.

In any of the embodiments disclosed herein the kit can includesingle-stranded oligonucleotides on one or more immobilized substrates.In some embodiments, the single-stranded oligonucleotides on one or moreimmobilized substrates can be used to enrich the samples for specificsequences by performing hybrid capture and removing the unbound nucleicacid molecules. In any of the embodiments disclosed herein the kit caninclude a container that holds a cell lysis buffer, tubes for performingcell lysis, and/or tubes for purifying DNA from a sample. In someembodiments, the cell lysis buffer, tubes and/or tubes can be designedfor specific types of cells or samples, such as circulating cell-freeDNA found in blood samples, including circulating cell-free fetal DNAand circulating cell-free tumor DNA.

Any of the kits disclosed herein can include an amplification reactionmixture comprising any of the following: a reaction buffer, dNTPs,dNTPs, and a polymerase. In some embodiments, the kit can include aligation buffer and a ligase. In any of the embodiments disclosedherein, the kit can also include a means for clonally amplifying taggednucleic acid molecules onto one or more solid supports. A skilledartisan will understand which components to include in a kit to enablethe use of such kits for the various methods herein.

Determining the Number of Copies of One or More Chromosomes orChromosome Segments of Interest

In some embodiments, methods provided herein for identifying individualsample nucleic acid molecules using MITs, can be used as part of methodsto determine the number of copies of one or more chromosomes orchromosome segments of interest in a sample. As demonstrated by themathematical proofs provided in Example 3, by using methods that includeMITs for identifying individual sample nucleic acid molecules as part ofmethods for determining the number of copies of one or more chromosomesor chromosome segments of interest in a sample, significant cost andsample savings can be achieved. For example, based on the reduced noiseand improved accuracy obtained with the use of MITs for identifyingindividual sample nucleic acid molecules demonstrated in Example 1, aslittle as 100 μl of plasma can be used to obtain results with anacceptable confidence. Furthermore, results with an acceptableconfidence can be attained with as few as 1,780,000 sequencing reads.Thus, two important limitations in current methods can be overcome:sample volume and cost.

The present disclosure is of use in, among other areas, thedetermination of the number of copies of one or more chromosomes orchromosome segments of interest in a sample, as disclosed herein.Methods for determining the number of chromosome(s) or chromosomesegments of interest that can be adapted for use in methods of thepresent disclosure include those disclosed, for example, in publishedU.S. patent application Ser. No. 13/499,086 filed Mar. 29, 2012; U.S.patent application Ser. No. 14/692,703 filed Apr. 21, 2015; U.S. patentapplication Ser. No. 14/877,925 filed Oct. 7, 2015; U.S. patentapplication Ser. No. 14/918,544 filed Oct. 20, 2015; “Noninvasiveprenatal detection and selective analysis of cell-free DNA obtained frommaternal blood: evaluation for trisomy 21 and trisomy 18” (Sparks et al.April 2012. American Journal of Obstetrics and Gynecology.206(4):319.e1-9); and “Detection of Clonal and Subclonal Copy-NumberVariants in Cell-Free DNA from Patients with Breast Cancer Using aMassively Multiplexed PCR Methodology” (Kirkizlar et al. October 2015.Translation Oncology. 8(5):407-416), which are each herein incorporatedby reference in their entireties.

Using MITs, a smaller sample volume of blood or a fraction thereof canbe required to obtain results with an acceptable confidence. In someembodiments, the sample of blood can be a maternal blood sample for usein noninvasive prenatal testing. This can reduce any effects on patientsand can reduce cost of sample preparation. In any of the embodimentsdisclosed herein the volume of the sample can be between 0.01, 0.02,0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.125, 0.15, 0.175, 0.2,0.25, 0.3, 0.35, 0.4, 0.45, and 0.5 ml on the low end of the range and0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.125, 0.15, 0.175, 0.2, 0.25, 0.3,0.35, 0.4, 0.45, 0.5, 0.6, 0.7, 0.8, 0.9, 1 1.25 1.5, 1.75, 2, 2.5, 3,3.5, 4, 4.5, and 5 ml on the high end of the range. In some embodiments,the sample volume is between 0.1, 0.125, 0.15, 0.175, 0.2, 0.25, 0.3,0.35, 0.4, 0.45, and 0.5 ml on the low end of the range and 0.25, 0.3,0.35, 0.4, 0.45, 0.5, 0.6, 0.7, 0.8, 0.9, 1 1.25 1.5, 1.75, 2, 2.5, and3 ml on the high end of the range.

In any of the embodiments disclosed herein, the sample can be a maternalblood sample that comprises circulating cell-free DNA from a fetus andthe mother of the fetus. In some embodiments, these samples are used toperform non-invasive prenatal testing. In other embodiments, the samplecan be a blood sample from a person having or suspected of havingcancer. In some embodiments, the circulating cell-free DNA can includeDNA fragments with lengths between 50, 60, 70, 80, 90, 100, 110, 120,130, 140, and 150 nucleotides on the low end of the range and 60, 70,80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, and 200nucleotides on the high end of the range.

In some embodiments, the lengths of any of the one or more chromosomesegments of interest can be between 100, 200, 300, 400, 500, 600, 700,800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000,10,000, 15,000, 20,000, 25,000, 50,000, 60,000, 70,000, 80,000, 90,000,and 100,000 nucleotides long on the low end of the range and 500, 600,700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000,9,000, 10,000, 15,000, 20,000, 25,000, 50,000, 60,000, 70,000, 80,000,90,000, 100,000, 200,000, 300,000, 400,000, 500,000, 600,000, 700,000,800,000, 900,000, 1,000,000, 1,000,000, 2,000,000, 3,000,000, 4,000,000,5,000,000, 6,000,000, 7,000,000, 8,000,000, 9,000,000, 10,000,000,15,000,000, 20,000,000, 25,000,000, 30,000,000, 40,000,000, 50,000,000,60,000,000, 70,000,000, 80,000,000, 90,000,000, 100,000,000,125,000,000, 150,000,000, 175,000,000, 200,000,000, 250,000,000, and300,000,000 nucleotides long on the high end of the range.

In one aspect, the present disclosure features methods for determiningthe number of copies of one or more chromosomes or chromosome segmentsof interest in a sample. In some embodiments, a method for determiningthe number of copies of one or more chromosomes or chromosome segmentsof interest in a sample of blood or a fraction thereof includes forminga reaction mixture of sample nucleic acid molecules and a set ofMolecular Index Tags (MITs) to generate a population of tagged nucleicacid molecules, wherein at least some of the sample nucleic acidmolecules comprise one or more target loci of a plurality of target locion the chromosome or chromosome segment of interest; amplifying thepopulation of tagged nucleic acid molecules to create a library oftagged nucleic acid molecules; determining the sequences of the attachedMITs and at least a portion of the sample nucleic acid segments of thetagged nucleic acid molecules in the library of tagged nucleic acidmolecules, to determine the identity of a sample nucleic acid moleculethat gave rise to a tagged nucleic acid molecule; measuring a quantityof DNA for each target locus by counting the number of sample nucleicacid molecules that comprise each target locus using the determinedidentities; measuring a quantity of DNA for each target locus bycounting the number of sample nucleic acid molecules that comprise eachtarget locus using the determined identities; determining, on acomputer, the number of copies of the one or more chromosomes orchromosome segments of interest using the quantity of DNA at each targetlocus in the sample nucleic acid molecules, wherein the number of targetloci and the volume of the sample provide an effective amount of totaltarget loci to achieve a desired sensitivity and a desired specificityfor the copy number determination. The total target loci, T_(L), can bedefined as the product of the total number of sample nucleic acidmolecules that span each target locus in a sample, C, and the number oftarget loci in the sample, L, such that T_(L)=C×L. The effective amount,EA, can be defined as the volume necessary to obtain a particular numberof total target loci for a target sensitivity and specificity. In someembodiments, the number of total target loci can be between 100, 200,300, 400, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000,6,000, 7,000, 8,000, 9,000, 10,000, 20,000, 30,000, 40,000, 50,000,75,000, and 100,000 total target loci on the low end of the range and500, 600, 700, 800, 900, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000,7,000, 8,000, 9,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000,100,000, 200,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000,900,000, 1,000,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000,6,000,000, 7,000,000, 8,000,000, 9,000,000, and 10,000,000 total targetloci on the high end of the range. The effective amount can take intoaccount the sample preparation efficiency and the fraction of DNA in amixed sample, for example, the fetal fraction in a maternal bloodsample. Tables 1 and 3 in Example 3 show the total number of sequencingreads, which are the same as the total target loci, required to obtain atarget sensitivity and specificity for different methods of the presentdisclosure. In some embodiments, the total number of sample nucleic acidmolecules in the population of sample nucleic acid molecules is greaterthan the diversity of MITs in the set of MITs. In further embodimentsthe sample comprises a mixture of two genetically distinct genomes. Forexample, the mixture can be a blood or plasma sample comprisingcirculating cell-free tumor DNA and normal DNA, or maternal DNA andfetal DNA.

Example 3 herein provides tables that identify a total number ofsequencing reads or total target loci needed for achieving a certainlevel of specificity and sensitivity at different percent mixtures(“Fraction of G2 in the sample”), which can be for example, the percentof cancer vs. normal DNA or the percent of fetal vs. maternal DNA. Totaltarget loci are identified by multiplying the number of target loci fora chromosome or chromosome segment by the number of haploid copies ofthe target loci provided by the sample volume. For example, asdemonstrated in Example 3, to achieve a 99% sensitivity and specificityin 4% of fetal DNA or circulating cell-free DNA, using a non-allelicmethod, requires 110,414 total target loci. This can be achieved using0.5 ml of plasma, a plurality of at least 1000 loci, and a sample prepmethod that retains at least 25% of the initial total target loci usinga set of at least 32 MITs. Thus, in this example, the effective amountis at least 1000 loci and at least 0.5 ml of plasma.

In some embodiments, determining the number of copies of the one or morechromosomes or chromosome segments of interest can include comparing thequantity of DNA at the plurality of target loci to a quantity of DNA ata plurality of disomic loci on one or more chromosomes or chromosomesegments expected to be disomic. The quantity of DNA at the plurality ofdisomic loci can be determined in the same manner as the plurality oftarget loci, i.e. determining the sequences of the attached MITs and atleast a portion of the sample nucleic acid segments of the taggednucleic acid molecules in the library of tagged nucleic acid moleculesand using the determined sequences to determine the identity of a samplenucleic acid molecule that gave rise to a tagged nucleic acid moleculeand measuring a quantity of DNA for each target locus by counting thenumber of sample nucleic acid molecules that comprise each target locususing the determined identities. In some embodiments, the plurality ofdisomic loci on the one or more chromosomes or chromosome segmentsexpected to be disomic can be SNP loci.

In any of the embodiments disclosed herein, the number of loci in theplurality of target loci can be between 10, 20, 30, 40, 50, 60, 70, 80,90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000,4,000, and 5,000 loci on the low end of the range and 50, 60, 70, 80,90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1,000, 2,000, 3,000,4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 20,000, 30,000,40,000, 50,000, 60,000, 70,000, 80,000, 90,000, and 100,000 loci on thehigh end of the range. In some embodiments, the number of target lociare at least 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000,9,000, or 10,000 loci. In any of the embodiments disclosed herein, thenumber of loci in the plurality of disomic loci can be between 10, 20,30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900,1,000, 2,000, 3,000, 4,000, and 5,000 loci on the low end of the rangeand 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900,1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000,20,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000, 90,000, and100,000 loci on the high end of the range. In some embodiments, thenumber of disomic loci are at least 1,000, 2,000, 3,000, 4,000, 5,000,6,000, 7,000, 8,000, 9,000, or 10,000 loci.

In various embodiments, a set of hypotheses concerning the number ofcopies of the one or more chromosomes or chromosome segments of interestcan be generated to compare the measured quantity of DNA to an expectedquantity of DNA based on each particular hypothesis. In the context ofthis disclosure, a hypothesis can refer to a copy number of a chromosomeor chromosome segment of interest. It may refer to a possible ploidystate. It may refer to a possible allelic state or allelic imbalance. Insome embodiments, a set of hypotheses may be designed such that onehypothesis from the set will correspond to the actual genetic state ofany given individual. In some embodiments, a set of hypotheses may bedesigned such that every possible genetic state may be described by atleast one hypothesis from the set. In some embodiments, of the presentdisclosure, the method can determine which hypothesis corresponds to theactual genetic state of the individual in question. In some embodiments,the set of hypotheses may include hypotheses of fetal fraction inaddition to the possible genetic state. In some embodiments, the set ofhypotheses may include hypotheses of in average allelic imbalance inaddition to the possible genetic state.

In some embodiments, a joint distribution model can be used to determinea relative probability of each hypothesis. A joint distribution model isa model that defines the probability of events defined in terms ofmultiple random variables, given a plurality of random variables definedon the same probability space, where the probabilities of the variableare linked. In some embodiments, the degenerate case where theprobabilities of the variables are not linked may be used. In variousembodiments of the present disclosure, determining the number of copiesof one or more chromosomes or chromosome segments of interest in asample also includes combining the relative probabilities of each of theploidy hypotheses determined using the joint distribution model withrelative probabilities of each of the ploidy hypotheses that arecalculated using statistical techniques taken from a group consisting ofa read count analysis, comparing heterozygosity rates, the probabilityof normalized genotype signals for certain parent contexts, andcombinations thereof. In various embodiments, the joint distribution cancombine the relative probabilities of each of the ploidy hypotheses withthe relative probabilities of each of the fetal fraction hypotheses. Insome embodiments, of the present disclosure, determining the relativeprobability of each hypothesis can make use of an estimated fraction ofthe DNA in the sample. In various embodiments, the joint distributioncan combine the relative probabilities of each of the ploidy hypotheseswith the relative probabilities of each of the allelic imbalancehypotheses. In some embodiments, determining the copy number of one ormore chromosomes or chromosome segments of interests includes selectingthe hypothesis with the greatest probability, which is carried out usinga maximum likelihood estimate technique or a maximum a posterioritechnique.

Maximum Likelihood and Maximum a Posteriori Estimates

Most methods known in the art for detecting the presence or absence ofbiological phenomenon or medical condition involve the use of a singlehypothesis rejection test, where a metric that is correlated with thecondition is measured, and if the metric is on one side of a giventhreshold, the condition is present, while of the metric falls on theother side of the threshold, the condition is absent. Asingle-hypothesis rejection test only looks at the null distributionwhen deciding between the null and alternate hypotheses. Without takinginto account the alternate distribution, one cannot estimate thelikelihood of each hypothesis given the observed data and therefore onecannot calculate a confidence on the call. Hence with asingle-hypothesis rejection test, one gets a yes or no answer without afeeling for the confidence associated with the specific case.

In some embodiments, the method disclosed herein is able to detect thepresence or absence of biological phenomenon or medical condition usinga maximum likelihood method. This is a substantial improvement over amethod using a single hypothesis rejection technique as the thresholdfor calling absence or presence of the condition can be adjusted asappropriate for each case. This is particularly relevant for diagnostictechniques that aim to determine the presence or absence of aneuploidyin a gestating fetus from genetic data available from the mixture offetal and maternal DNA present in the free floating DNA found inmaternal plasma. This is because as the fraction of fetal DNA in theplasma derived fraction changes, the optimal threshold for callinganeuploidy versus euploidy changes. As the fetal fraction drops, thedistribution of data that is associated with an aneuploidy becomesincreasingly similar to the distribution of data that is associated witha euploidy.

The maximum likelihood estimation method uses the distributionsassociated with each hypothesis to estimate the likelihood of the dataconditioned on each hypothesis. These conditional probabilities can thenbe converted to a hypothesis call and confidence. Similarly, the maximuma posteriori estimation method uses the same conditional probabilitiesas the maximum likelihood estimate, but also incorporates populationpriors when choosing the best hypothesis and determining confidence.Therefore, the use of the maximum likelihood estimate (MLE) technique orthe closely related maximum a posteriori (MAP) technique gives twoadvantages, first it increases the chance of a correct call, and it alsoallows a confidence to be calculated for each call.

Exemplary Methods of Determining the Number of Sample Nucleic AcidMolecules

A method is disclosed herein to determine the number of DNA molecules ina sample by generating a tagged nucleic acid molecule from each samplenucleic acid molecule by incorporating two MITs. Disclosed here is aprocedure to accomplish the above end followed by a single molecule orclonal sequencing method.

As detailed herein, the approach entails generating tagged nucleic acidmolecules such that most or all of the tagged nucleic acid moleculesfrom each locus have different combinations of MITs and can beidentified upon sequencing of the MITs using clonal or single moleculesequencing. The identification can optionally use the mapped locationsof the nucleic acid segments. Each combination of MITs and nucleic acidsegment represents a different sample nucleic acid molecule. Using thisinformation one can determine the number of individual sample nucleicacid molecules in the original sample for each locus.

This method can be used for any application in which quantitativeevaluation of the number of sample nucleic acid molecules is required.Furthermore, the number of individual nucleic acid molecules from one ormore target loci can be related to the number of individual nucleic acidmolecules from one or more disomic loci to determine the relative copynumber, copy number variation, allele distribution, allele ratio,allelic imbalance, or average allelic imbalance. Alternatively, thenumber of copies detected from various targets can be modeled by adistribution in order to identify the mostly likely number of copies ofthe target loci. Applications include but are not limited to detectionof insertions and deletions such as those found in carriers of DuchenneMuscular Dystrophy; quantitation of deletions or duplications segmentsof chromosomes such as those observed in copy number variants;determination of chromosome copy number of samples from bornindividuals; and determination of chromosome copy number of samples fromunborn individuals such as embryos or fetuses.

The method can be combined with simultaneous evaluation of variationscontained in the determined sequences. This can be used to determine thenumber of sample nucleic acid molecules representing each allele in theoriginal sample. This copy number method can be combined with theevaluation of SNPs or other sequence variations to determine the copynumber of chromosomes or chromosome segments of interest from born orunborn individuals; the discrimination and quantification of copies fromloci which have short sequence variations, but in which PCR may amplifyfrom multiple target loci such as in carrier detection of Spinal MuscleAtrophy; and determination of copy number of different sources ofnucleic acid molecules from samples consisting of mixtures of differentindividuals such as in the detection of fetal aneuploidy from freefloating DNA obtained from maternal plasma.

In any of the embodiments disclosed herein the method may comprise oneor more of the following steps: (1) Attaching Y-adaptor nucleic acidmolecules with MITs to a population of sample nucleic acid molecules byligation. (2) Performing one or more rounds of amplification. (3) Usinghybrid capture to enrich target loci. (4) Measuring the amplified PCRproduct by a multitude of methods, for example, clonal sequencing, to asufficient number of bases to span the sequence.

In any of the embodiments disclosed herein the method as it pertains toa single target locus may comprise one or more of the following steps:(1) Designing a standard pair of oligomers for amplification of aspecific locus. (2) Adding, during synthesis, a sequence of specifiedbases, with no or minimal complementarity to the target locus or genome,to the 5′ end of both of the target specific PCR primers. This sequence,termed the tail, is a known sequence, to be used for subsequentamplification, followed by an MIT. Consequently, following synthesis,the tailed PCR primer pool will consist of a collection of oligomersbeginning with a known sequence followed by the MIT, followed by thetarget specific sequence. (3) Performing one round of amplification(denaturation, annealing, extension) using only the tailed oligomer. (4)Adding exonuclease to the reaction, effectively stopping the PCRreaction, and incubating the reaction at the appropriate temperature toremove forward single stranded oligos that did not anneal to temple andextend to form a double stranded product. (5) Incubating the reaction ata high temperature to denature the exonuclease and eliminate itsactivity. (6) Adding to the reaction a new oligonucleotide that iscomplementary to the tail of the oligomer used in the first reactionalong with the other target specific oligomer to enable PCRamplification of the product generated in the first round of PCR. (7)Continuing amplification to generate enough product for downstreamclonal sequencing. (8) Measuring the amplified PCR product by amultitude of methods, for example, clonal sequencing, to a sufficientnumber of bases to span the sequence.

In some embodiments, the design and generation of primers with MITs maybe reduced to practice as follows: the primers with MITs may consist ofa sequence that is not complementary to the target sequence followed bya region with the MIT followed by a target specific sequence. Thesequence 5′ of the MIT may be used for subsequent PCR amplification andmay comprise sequences useful in the conversion of the amplicon to alibrary for sequencing. In some embodiments, the DNA can be measured bya sequencing method, where the sequence data represents the sequence ofa single molecule. This can include methods in which single moleculesare sequenced directly or methods in which single molecules areamplified to form clones detectable by the sequence instrument, but thatstill represent single molecules, herein called clonal sequencing.

In some embodiments, a method of the present disclosure involvestargeting multiple loci in parallel or otherwise. Primers to differenttarget loci can be generated independently and mixed to create multiplexPCR pools. In some embodiments, original samples can be divided intosubpools and different loci can be targeted in each sub-pool beforebeing recombined and sequenced. In some embodiments, the tagging stepand a number of amplification cycles may be performed before the pool issubdivided to ensure efficient targeting of all targets beforesplitting, and improving subsequent amplification by continuingamplification using smaller sets of primers in subdivided pools.

For example, imagine a heterozygous SNP in the genome of an individual,and a mixture of DNA from the individual where ten sample nucleic acidmolecules of each allele are present in the original sample of DNA.After MIT incorporation and amplification there may be 100,000 taggednucleic acid molecules corresponding to that locus. Due to stochasticprocesses, the ratio of DNA could be anywhere from 1:2 to 2:1, however,since each of the sample nucleic acid molecules was tagged with MITs, itwould be possible to determine that the DNA in the amplified pooloriginated from exactly 10 sample nucleic acid molecules from eachallele. This method would therefore give a more accurate measure of therelative amounts of each allele than a method not using this approach.For methods where it is desirable for the relative amount of allele biasto be minimized, this method will provide more accurate data.

Association of the sequenced fragment to the target locus can beachieved in a number of ways. In some embodiments, a sequence ofsufficient length is obtained from the targeted fragment to span the MITas well a sufficient number of unique bases corresponding to the targetsequence to allow unambiguous identification of the target locus. Inother embodiments, the MIT primer that contains the MIT can also containa locus specific barcode (locus barcode) that identifies the target towhich it is to be associated. This locus barcode would be identicalamong all MIT primers for each individual target locus and hence allresulting amplicons, but different from all other loci. In someembodiments, the tagging method disclosed herein may be combined with aone-sided nesting protocol.

One example of an application where MITs would be particularly usefulfor determining copy number is non-invasive prenatal aneuploidydiagnosis where the quantity of DNA at a target locus or plurality oftarget loci can be used to help determine the number of copies of one ormore chromosomes or chromosome segment of interest in a fetus. In thiscontext, it is desirable to amplify the DNA present in the initialsample while maintaining the relative amounts of the various alleles. Insome circumstances, especially in cases where there is a very smallamount of DNA, for example, fewer than 5,000 copies of the genome, fewerthan 1,000 copies of the genome, fewer than 500 copies of the genome,and fewer than 100 copies of the genome, one can encounter a phenomenoncalled bottlenecking. This is where there are a small number of copiesof any given allele in the initial sample, and amplification biases canresult in the amplified pool of DNA having significantly differentratios of those alleles than are in the initial mixture of DNA. By usingMITs on each strand of DNA before standard PCR amplification, it ispossible to exclude n−1 copies of DNA from a set of n identicalsequenced tagged nucleic acid molecules in the library that originatedfrom the same sample nucleic acid molecule. In this manner, any allelicbias or amplification bias can be removed from further analysis. Invarious embodiments, of the present disclosure, the method may beperformed for fetuses at between 4 and 5 weeks gestation; between 5 and6 weeks gestation; between 6 and 7 weeks gestation; between 7 and 8weeks gestation; between 8 and 9 weeks gestation; between 9 and 10 weeksgestation; between 10 and 12 weeks gestation; between 12 and 14 weeksgestation; between 14 and 20 weeks gestation; between 20 and 40 weeksgestation; in the first trimester; in the second trimester; in the thirdtrimester; or combinations thereof.

Another application where MITs would be particularly useful fordetermining copy number or average allelic imbalance is non-invasivecancer diagnosis where the amount of genetic material at a locus or aplurality of loci can be used to help determine copy number variationsor average allelic imbalances. Allelic imbalance for aneuploidydeterminations, such as copy number variant determinations, refers tothe difference between the frequencies of the alleles for a locus. It isan estimate of the difference in the numbers of copies of the homologs.Allelic imbalance can arise from the complete loss of an allele or froman increase in copy number of one allele relative to the other. Allelicimbalances can be detected by measuring the proportion of one allelerelative to the other in fluids or cells from individuals that areconstitutionally heterozygous at a given locus. (Mei et al, Genome Res,10:1126-37 (2000)). For dimorphic SNPs that have alleles arbitrarilydesignated ‘A’ and ‘B’, the allele ratio of the A allele is nA/(nA+nB),where nA and nB are the number of sequencing reads for alleles A and B,respectively. Allelic imbalance is the difference between the alleleratios of A and B for loci that are heterozygous in the germline. Thisdefinition is analogous to that for SNVs, where the proportion ofabnormal DNA is typically measured using mutant allele frequency, ornm/(nm+nr), where nm and nr are the number of sequencing reads for themutant allele and the reference allele, respectively. Accordingly, theproportion of abnormal DNA for a CNV can be measured by the averageallelic imbalance (AAI), defined as |(H1−H2)|/(H1+H2), where Hi is theaverage number of copies of homolog i in the sample and Hi/(H1+H2) isthe fractional abundance, or homolog ratio, of homolog i. The maximumhomolog ratio is the homolog ratio of the more abundant homolog.

Accurately Measuring the Allelic Distributions in a Sample

Current sequencing approaches can be used to estimate the distributionof alleles in a sample. One such method involves randomly samplingsequences from a pool DNA, termed shotgun sequencing. The proportion ofa particular allele in the sequencing data is typically very low and canbe determined by simple statistics. The human genome containsapproximately 3 billion base pairs. So, if the sequencing method usedmake 100 bp reads, a particular allele will be measured about once inevery 30 million sequence reads.

In some embodiments, a method of the present disclosure is used todetermine the presence or absence of two or more different haplotypesthat contain the same set of loci in a sample of DNA from the measuredallele distributions of loci from that chromosome. The differenthaplotypes could represent two different homologous chromosomes from onesource, three different homologous chromosomes from one, three differenthomologous haplotypes in a sample comprising a mixture of twogenetically distinct genomes where one of the haplotypes is sharedbetween the genetically distinct genomes, three or four haplotypes in asample comprising a mixture of two genetically distinct genomes whereone or two of the haplotypes are shared between the genetically distinctgenomes, or other combinations. Alleles that are polymorphic between thehaplotypes tend to be more informative, however any alleles where thegenetically distinct genomes are not both homozygous for the same allelewill yield useful information through measured allele distributionsbeyond the information that is available from simple read countanalysis.

Shotgun sequencing of such a sample, however, is extremely inefficientas it results in reads for many sequences from loci that are notpolymorphic between the different haplotypes in the sample, or are forchromosomes that are not of interest, and therefore reveal noinformation about the proportion of the target haplotypes. Disclosedherein are methods that specifically target and/or preferentially enrichsegments of DNA in the sample that are more likely to be polymorphic inthe genome to increase the yield of allelic information obtained bysequencing. Note that for the measured allele distributions in anenriched sample to be truly representative of the actual amounts presentin the target individual, it is critical that there is little or nopreferential enrichment of one allele as compared to the other allele ata given locus in the targeted segments. Current methods known in the artto target polymorphic alleles are designed to ensure that at least someof any alleles present are detected. However, these methods were notdesigned for the purpose of measuring the unbiased allelic distributionsof polymorphic alleles present in the original mixture. It is difficultto predict that a particular method of target enrichment would producean enriched sample wherein the measured allele distributions wouldaccurately represent the allele distributions present in the originalunamplified sample better than another method. While many enrichmentmethods may be expected, in theory, to accomplish such an aim, there isa great deal of stochastic bias in current amplification, targeting, andother preferential enrichment methods. One embodiment of a methoddisclosed herein allows a plurality of alleles found in a mixture of DNAthat correspond to a given locus in the genome to be amplified, orpreferentially enriched in a way that the degree of enrichment of eachof the alleles is nearly the same. Another way to say this is that themethod allows the relative quantity of the alleles present in themixture as a whole to be increased, while the ratio between the allelesthat correspond to each locus remains essentially the same as they werein the original mixture of DNA. For some reported methods, preferentialenrichment of loci can result in allelic biases of more than 1%, morethan 2%, more than 5% and even more than 10%. This preferentialenrichment may be due to capture bias when using a hybrid captureapproach, or amplification bias which may be small for each cycle, butcan become large when compounded over 20, 30, or 40 cycles. For thepurposes of this disclosure, for the ratio to remain essentially thesame means that the ratio of the alleles in the original mixture dividedby the ratio of the alleles in the resulting mixture is between 0.95 and1.05, between 0.98 and 1.02, between 0.99 and 1.01, between 0.995 and1.005, between 0.998 and 1.002, between 0.999 and 1.001, or between0.9999 and 1.0001. Note that the calculation of the allele ratiospresented here may not be used in the determination of the ploidy stateof the target individual, and may only be used as a metric to measureallelic bias. The use of MITs can be used to remove errors due tocapture bias, amplification bias, and allelic bias as the number ofsample nucleic acid molecules can be specifically counted using themethods disclosed herein.

In some embodiments, once a mixture has been preferentially enriched atthe set of target loci, it may be sequenced using any one of theprevious, current, or next generation of sequencing instruments asdiscussed in more detail herein. The ratios can be evaluated bysequencing through the specific alleles within the chromosome orchromosome segment of interest. These sequencing reads can be analyzedand counted according the allele type and the ratios of differentalleles determined accordingly. For variations that are one to a fewbases in length, detection of the alleles will be performed bysequencing and it is essential that the sequencing read span the allelein question in order to evaluate the allelic composition of thatcaptured molecule. The total number of captured nucleic acid moleculesassayed for the genotype can be increased by increasing the length ofthe sequencing read. Full sequencing of all tagged nucleic acidmolecules would guarantee collection of the maximum amount of dataavailable in the enriched pool. However, sequencing is currentlyexpensive, and a method that can measure allele distributions using alower number of sequence reads will have great value. In addition, thereare technical limitations to the maximum possible length of read as wellas accuracy limitations as read lengths increase. The alleles ofgreatest utility will be of one to a few bases in length, buttheoretically any allele shorter than the length of the sequencing readcan be used. Larger variants such as segmental copy number variants canbe detected by aggregations of these smaller variations in many cases aswhole collections of SNP internal to the segment are duplicated.Variants larger than a few bases, such as STRs require specialconsideration and some targeting approaches work while others will not.

There are multiple targeting approaches that can be used to specificallyisolate and enrich one or a plurality of variant positions in thegenome. Typically, these rely on taking advantage of the invariantsequence flanking the variant sequence. There are reports by othersrelated to targeting in the context of sequencing where the substrate ismaternal plasma (see, e.g., Liao et al., Clin. Chem. 2011; 57(1): pp.92-101). However, these approaches use targeting probes that targetexons, and do not focus on targeting polymorphic loci of the genome. Invarious embodiments, a method of the present disclosure involves usingtargeting probes that focus exclusively or almost exclusively onpolymorphic loci. In some embodiments, a method of the presentdisclosure involves using targeting probes that focus exclusively oralmost exclusively on SNPs. In some embodiments, of the presentdisclosure, the targeted polymorphic sites consist of at least 10% SNPs,at least 20% SNPs, at least 30% SNPs, at least 40% SNPs, at least 50%SNPs, at least 60% SNPs, at least 70% SNPs, at least 80% SNPs, at least90% SNPs, at least 95% SNPs, at least 98% SNPs, at least 99% SNPs, atleast 99.9% SNPs, or exclusively SNPs.

In some embodiments, a method of the present disclosure can be used todetermine genotypes (base composition of the DNA at specific loci) andrelative proportions of those genotypes from a mixture of DNA molecules,where those DNA molecules may have originated from one or a number ofgenetically distinct genomes. In some embodiments, a method of thepresent disclosure can be used to determine the genotypes at a set ofpolymorphic loci, and the relative ratios of the amounts of differentalleles present at those loci. In some embodiments, the polymorphic locimay consist entirely of SNPs. In some embodiments, the polymorphic locican comprise SNPs, single tandem repeats, and other polymorphisms. Insome embodiments, a method of the present disclosure can be used todetermine the relative distributions of alleles at a set of polymorphicloci in a mixture of DNA, where the mixture of DNA comprises DNA thatoriginates from an individual and from a tumor growing in thatindividual.

In some embodiments, the mixture of DNA molecules could be derived fromDNA extracted from multiple cells of one individual. In someembodiments, the original collection of cells from which the DNA isderived may comprise a mixture of diploid or haploid cells of the sameor of different genotypes, if that individual is mosaic (germline orsomatic). In some embodiments, the mixture of nucleic acid moleculescould also be derived from DNA extracted from single cells. In someembodiments, the mixture of DNA molecules could also be derived from DNAextracted from a mixture of two or more cells of the same individual, orof different individuals. In some embodiments, the mixture of DNAmolecules could be derived from cell-free DNA, such as present in bloodplasma. In some embodiments, this biological material may be a mixtureof DNA from one or more individuals, as is the case during pregnancywhere it has been shown that fetal DNA is present in the mixture or incancer, when tumor DNA and can be present in the blood plasma. In someembodiments, the biological material could be from a mixture of cellsthat were found in maternal blood, where some of the cells are fetal inorigin. In some embodiments, the biological material could be cells fromthe blood of a pregnant which have been enriched in fetal cells.

The algorithm used to determine the number of copies of one or morechromosomes or chromosome segments of interest can consider parentalgenotypes and crossover frequency data (such as data from the HapMapdatabase) to calculate expected allele distributions for the target locifor a very large number possible fetal ploidy states, and at variousfetal cfDNA fractions. Unlike allele ratio based-methods, it can alsotake into account linkage disequilibrium and use non-Gaussian datamodels to describe the expected distribution of allele measurements at aSNP given observed platform characteristics and amplification biases.The algorithm can then compare the various predicted alleledistributions to the actual allelic distributions as measured in thesample, and can calculate the likelihood of each hypothesis (monosomy,disomy, or trisomy, for which there are numerous hypotheses based on thevarious potential crossovers) based on the sequencing data. Thealgorithm sums the likelihoods of each individual monosomy, disomy, ortrisomy hypothesis and calls the hypothesis with the maximum overalllikelihood as the copy number and fetal fraction. A similar algorithmcan be used to determine the average allelic imbalance in a sample and askilled artisan will understand how to modify the method.

The following examples are put forth so as to provide those of ordinaryskill in the art with a complete disclosure and description of how touse the embodiments provided herein, and are not intended to limit thescope of the disclosure nor are they intended to represent that theExamples below are all or the only experiments performed. Efforts havebeen made to ensure accuracy with respect to numbers used (e.g. amounts,temperature, etc.) but some experimental errors and deviations should beaccounted for. Unless indicated otherwise, parts are parts by volume,and temperature is in degrees Centigrade. It should be understood thatvariations in the methods as described can be made without changing thefundamental aspects that the Examples are meant to illustrate.

EXAMPLES Example 1. Exemplary Workflow for Identifying Sample NucleicAcid Molecules

Provided herein is an example of a method for identifying sample nucleicacid molecules after amplification of such molecules in ahigh-throughput sequencing workflow. The structure of a non-limitingexemplary amplicon produced using such a method is shown in FIG. 3. Aset of nucleic acid samples are prepared by isolating nucleic acids froma natural source. For example, circulating cell-free DNA can be isolatedfrom samples of blood, or a fraction thereof, from target patients usingknown methods. Some of the sample nucleic acids in the blood can includeone or more target sites. Sample nucleic acid molecules are processed sothat any overhangs are removed in a blunt end repair reaction usingKlenow large fragment, and polynucleotide kinase is used to ensure thatall 5′ ends are phosphorylated. A 3′ adenosine residue is added to theblunt end repaired sample nucleic acid molecules using Klenow Fragment(exo-) to increase ligation efficiency. A set of 206 MITs that are 6nucleotides in length, each having at least 2 base difference from allother MITs, are then designed to be included in the double-strandedpolynucleotide sequence adjacent to the 3′ T overhang of a standardhigh-throughput sequencing Y-adapter, as illustrated in FIG. 1. The setof Y-adapters each including a different MIT are then ligated to bothends of each sample nucleic acid molecule using a ligase, in a ligationreaction to produce a population of tagged nucleic acid molecules. Forthe ligation reaction 10,000 sample nucleic acid molecules are taggedwith the library of 206 MIT-containing Y-adapters. The resultingpopulation of tagged nucleic acid molecules includes a Y-adapter with anMIT ligated to both ends of the sample nucleic acid molecule asillustrated in FIG. 1, such that the MITs are ligated to the ends of thesample nucleic acid segment, also called the insert, of the taggednucleic acid molecule.

A library of tagged nucleic acid molecules is then prepared byamplifying the population of tagged nucleic acid molecules usinguniversal primers that bind to primer binding sites on the Y-adapters. Atarget enrichment step is then performed to isolate and amplify taggednucleic acid molecules that include sample nucleic acid segments withtarget SNPs. The target enrichment can be performed using a one-sidedPCR reaction or hybrid capture. Either of these target enrichmentreactions can be a multiplex reaction using a population of primers(one-sided PCR) or probes (hybrid capture) that are specific for asample nucleic acid segment that includes a target SNP. One or moreadditional PCR reactions are then performed using universal primers thatinclude a different barcode sequence for each patient sample, as well asclonal amplification and sequencing primer binding sequences (R-Tag andF-Tag in FIG. 3). The structure of resulting amplified tagged nucleicacid molecules is shown schematically in FIG. 3.

The amplified tagged nucleic acid molecules are then clonally amplifiedonto a solid support using universal sequences added during one of theamplification reactions. The sequence of the clonally amplified taggednucleic acid molecules is then determined on a high-throughputsequencing instrument, such as an Illumina sequencing instrument. Fortagged nucleic acid molecules enriched using one-sided PCR, the MIT onthe right side of the sample nucleic acid segment (i.e. insert) is thefirst base read by one of the sequencing reads. For tagged nucleic acidmolecules enriched using hybrid capture, one MIT remains on each side ofthe sample nucleic acid segment (i.e. insert) and the first base of afirst ligated MIT on one end of the sample nucleic acid segment is thefirst base read in a first read and the second ligated MIT at the otherend of the sample nucleic acid segment is the first base read in asecond read. The resulting sequencing reads are then analyzed. Thesequences of the fragment-specific insert ends are used to map thelocations of each end of the nucleic acid segment to specific locationsin the genome of the organism and these locations can be used incombination with the MITs to identify each tagged nucleic acid molecule.This information is then analyzed using commercially available softwarepackages that are programmed to differentiate true sequence differencesin sample nucleic acid molecules from errors that were introduced duringany of the sample preparation amplification reactions.

Example 2. Reduction of Error Rate Using MITs on Sample Nucleic AcidMolecules

Provided herein is an example demonstrating the reduction of error ratesprovided by using MITs to identify amplification errors in ahigh-throughput sequencing sample preparation workflow. Three separateexperiments were performed where, in each experiment, two independentDNA samples with 2×10¹¹ total sample nucleic acid molecules including10,000 input copies of the human genome (10,000 copies×(3,000,000,000bp/genome)/(150 bp/nucleic acid molecule)=2×10¹¹ total sample nucleicacid molecules) in 58 μl (5.75 nM final concentration) were used togenerate a library of tagged nucleic acid molecules with an MIT at the5′ end and an MIT at the 3′ end as disclosed herein. A set of 196 MITswas used for this experiment at a concentration between 0.5 and 2 μMsuch that the ratio of the total number of MITs in the reaction mixturesto the total number of sample nucleic acid molecules in the reactionmixtures was between ˜85:1 and ˜350:1. As indicated, only 196 MITs, orabout 40,000 combinations of two MITs, were used for a sample having2×10¹¹ total sample nucleic acid molecules.

In each experiment the libraries were enriched for tagged nucleic acidmolecules containing TP53 exons by performing hybrid capture with acommercially available kit. The enriched libraries were then amplifiedby PCR using universal primers that could bind to universal primerbinding sequences that had been previously incorporated into the taggednucleic acid molecules. The universal primers included different barcodesequences for each sample as well as additional sequences to enablesequencing on an Illumina HiSeq 2500. For each experiment the sampleswere then pooled and paired-end sequencing was performed on a HiSeq 2500in rapid mode for 150 cycles in each the forward and reverse read.

Sequencing data were demultiplexed using commercially availablesoftware. From each sequencing read, data for bases the length of theMIT plus the T overhang (seven nucleotides in total in theseexperiments) were trimmed from the start of the read and recorded. Theremaining trimmed read data were then merged and mapped to the humangenome. Fragment end positions for each read were recorded. All readswith at least one base covering the target locus (TP53 exons) wereconsidered on-target reads. The mean depths of read were calculated on aper base level across the target locus. Mean error rates (expressed aspercentages) were calculated by counting all base calls across thetarget locus that did not correspond to the reference genome (GRCh37)and dividing these by the total base calls across the target locus. Foreach base position in the target locus, sequencing data were thengrouped into MIT families where each MIT family shared identical MITs inthe same relative position to the analyzed base position as well as thesame fragment end positions and the same sequenced orientation (positiveor negative relative to the human genome). Each of these familiesrepresented groupings of molecules that are likely clonal amplificationsof the same sample nucleic acid molecule that entered the MIT librarypreparation process. Each sample nucleic acid molecule that entered intothe MIT library preparation process should have generated two families,one mapping to each of the positive and negative genomic orientations.Paired MIT nucleic acid segment families were then generated using twoMIT families, one with a positive orientation and one with a negativeorientation where each family contained complementary MITs in the samerelative position to the analyzed base position as well as thecomplementary fragment end positions. These paired MIT familiesrepresented groupings of sequenced molecules that are even more likelyto be clonal amplifications of the same sample nucleic acid moleculethat entered the MIT library preparation process. Mean error rates(expressed as percentages) were then calculated by counting all basecalls within all paired MIT nucleic acid segment families across thetarget locus that did not correspond to the reference genome (GRCh37)and dividing these by the total base calls within all paired MITfamilies across the target locus.

FIG. 4 shows the results of the three experiments. Each sample contained33 ng of DNA representing 10,000 input copies of the haploid humangenome. Sequencing data from these experiments yielded between 4.4million and 10.7 million mapped reads per sample and 3.0 million to 7.8million on-target reads per sample. The proportion of on-target reads tomapped reads ranged from 68% to 74%. The mean depth of read across thetarget loci ranged from ˜98,000 to −244,000 depth of read. Mean errorrates ranged from 0.15% to 0.26% if all the data was included. Meanerror rates calculated using data from only the paired MIT nucleic acidsegment families ranged from 0.0036% to 0.0067%. The average mean errorrate and paired MIT nucleic acid segment family error rate of the twosamples in each experiment show the drastic reduction in error rate whenpaired MIT nucleic acid segment families are used (FIG. 5). The residualerrors observed here are likely due to single nucleotide polymorphismsin the samples as these positions were not excluded. The paired MITnucleic acid segment family error rates were 23 to 73 times lower thantheir original error rates. Notably, experiments B and C, which hadhigher original error rates compared to experiment A, experiencedgreater reductions in error rates when calculated using the paired MITfamilies. These results demonstrate the utility of MITs for removal oferrors.

Example 3. Mathematical Analysis Demonstrating Low Sample Volumes forDetermining Copy Numbers Using MITs

This example provides an analysis of the number of target loci andplasma sample volume that provides an effective amount of total targetloci to achieve a desired sensitivity and a desired specificity for acopy number determination using MITs. In a sample with a mixture of twogenomes, G1 and G2, the copy numbers of chromosomes or chromosomesegments of interest can be determined for one of the genomes. G1 and G2can have various copy numbers of chromosomes of interest, for example,two copies of each chromosome in a set of chromosomes, one copy ofanother set, etc. Suppose G2 has one or more reference chromosomes orchromosome segments on its genome with known copy numbers (typically oneor more chromosomes or chromosome segments expected to be disomic) andone or more chromosomes or chromosome segments of interest on its genomewith unknown copy numbers (although the possible copy numbers areassumed to be known). The copy number of G2 of a chromosome orchromosome segment of interest where the true copy number is unknown canbe estimated (given the set of possible copy numbers are known). Notethat the copy numbers of G1 is known on both reference chromosomes orchromosome segments and chromosomes or chromosome segments of interest.The measurement technology is modeled as capturing a nucleic acidmolecule and identifying whether it belongs to the one or more referencechromosomes or chromosome segments or the one or more chromosomes orchromosome segments of interest, where there is probability of error.

Assuming that the sample contains a finite number of nucleic acidmolecules, we can sample nucleic acid molecules until we have a goodestimate of the number of nucleic acid molecules in the sample thatbelong to the one or more reference chromosomes or chromosome segmentsand the one or more chromosomes or chromosome segments of interest.Using an estimate of the fraction of G2 in the sample, test statisticsfor different copy number hypotheses of G2 in the one or morechromosomes or chromosome segments of interest can be calculated asdemonstrated below.

Method 1 Quantitative Non-Allelic Method

In this method, the number of sample nucleic acid molecules are comparedfor the one or more reference chromosomes or chromosome segments versusthe one or more chromosomes or chromosome segments of interest. Theassumptions are that when tagged nucleic acid molecules are sequenced,there is an equal probability of sequencing a tagged nucleic acidmolecule from the one or more reference chromosomes or chromosomesegments and the one or more chromosomes or chromosome segments ofinterest. Denote this probability with p, where p=0.5. An example of atest statistic that can be used is the ratio of number of nucleic acidmolecules from the one or more chromosomes or chromosome segments ofinterest (n_(t)) to the total number of observed nucleic acid molecules(n):

$T = \frac{n_{t}}{n}$

For n>20, the distribution of T can be approximated by a normaldistribution, with variance

$\frac{p\left( {1 - p} \right)}{n} = \frac{0.25}{n}$for p=0.5. The mean of the distribution depends on the copy numberhypothesis of G2 being tested and by getting more observations (i.e., bylowering the variance), one can increase the accuracy of the results.This allows for creating an estimator that achieves particularsensitivity and specificity.

Suppose that G2 represents 4% of the sample mixture (and G1 is 96% ofthe mixture). Further, assume that G1 has two copies of each locus inboth the reference chromosomes or chromosome segments and chromosomes orchromosome segments of interest. Also, assume that G2 has two copies ofeach locus in the one or more reference chromosomes or chromosomesegments. We want to consider two hypotheses: H2, where G2 has twocopies of each locus in a chromosome or chromosome segment of interestand H3, where G2 has three copies of each locus in the chromosome orchromosome segment of interest. As mentioned above, we can use thenormal distribution to estimate the distribution of the test statisticabove. The mean of the test statistic for H2 is 0.5, because the copynumbers of both G1 and G2 are identical on the reference chromosomes orchromosome segments and chromosomes or chromosome segments of interest.The mean of the test statistic for H3 is:

$\frac{{\left( {1 - {4\%}} \right)/2} + {{3/4}*4\%}}{{1/2} + {{1/2}*\left( {1 - {4\%}} \right)} + {{3/4}*4\%}} = 0.50495$

We use the usual notation of N(μ,σ²) to denote the normal distributionwith mean μ and variance σ². Therefore, the distributions of the teststatistic for the two hypotheses are:

H2: N(0.5,0.25/n)

H3: N(0.50495,0.25/n)

With this information, we can calculate what n is needed to attain aparticular sensitivity and specificity. Suppose we want sensitivity andspecificity to be 99%, we know that given a normal distribution, X, withmean 0 and variance 1, Prob(X<−2.326)=1%. We therefore solve for thefollowing,

$\frac{\left( {0.5 - 0.505} \right)/2}{0.5/\sqrt{n}} < {- 2.326}$

to obtain n>220,827. Therefore, we need approximately 110,414observations for each chromosome or chromosome segment. See Table 1 forthe number of observations needed for each of the one or more referencechromosomes or chromosome segments and the one or more chromosomes orchromosome segments of interest for a range of mixture fractions andtarget sensitivity and specificity.

TABLE 1 Sequencing reads required for method 1 using various fractionsof G2 in the sample and different target sensitivities andspecificities. Target Sensitivity and Specificity 99.9% 99.5% 99% 98%95% 90% Fraction 0.5%  12,253,983 8,513,913 6,944,554 5,412,3983,471,759 2,107,498 of G2 in  1% 3,071,150 2,133,796 1,740,476 1,356,480870,108 528,191 the sample  2% 771,622 536,113 437,292 340,814 218,613132,707  3% 344,651 239,459 195,320 152,227 97,645 59,275  4% 194,830135,365 110,413 86,053 55,198 33,508  5% 125,309 87,063 71,015 55,34735,502 21,551  6% 87,450 60,759 49,560 38,626 24,776 15,040  7% 64,56644,860 36,591 28,518 18,293 11,104  8% 49,677 34,515 28,153 21,94114,074 8,544  9% 39,443 27,405 22,353 17,422 11,175 6,784 10% 32,10622,307 18,195 14,181 9,096 5,522 15% 14,619 10,157 8,285 6,457 4,1422,514 20% 8,423 5,852 4,773 3,720 2,386 1,449 25% 5,520 3,835 3,1282,438 1,564 949 30% 3,924 2,726 2,224 1,733 1,112 675 35% 2,950 2,0501,672 1,303 836 507 40% 2,311 1,606 1,310 1,021 655 397 45% 1,868 1,2981,058 825 529 321 50% 1,547 1,075 877 683 438 266Method 2 Using Allele Ratios

Similar to the quantitative approach described in Method 1, amolecule-based method that looks at the heterozygous rate at known SNPscan be used. In this approach, the test statistic for a SNP on the oneor more chromosomes or chromosome segments of interest which can take onan allele value of A or B would be the observed rate of referencealleles. In particular, for a given SNP, let A and B denote the numberof observed molecules with an A and B allele respectively. We can thendefine the heterozygous rateH=AA+B

and the number of molecules at the SNP asN=A+B.

Let A₁ and A₂ denote the number of A alleles in genome G1 and G2,respectively, at the SNPs of interest. Similarly, B₁ and B₂ denote thenumber of B alleles in genome G1 and G2, respectively, at the SNPs ofinterest. The distribution of A is then a binomial distribution whoseparameters are functions of A₁, A₂, B₁, B₂, and N. We assume that A₁ andB₁ are known and we want to estimate A₂ and B₂. We can do this bycalculating the probability of the observed heterozygous rate H for allpossible values of A₂ and B₂ and using Bayes rule to compute aprobability of A₂ and B₂ given our observed H. For example, suppose thatG2 represents 4% of the sample mixture (therefore, G1 is 96% of themixture). Further, assume that G1 has two copies of each locus in thereference chromosomes or chromosome segments and the chromosomes orchromosome segments of interest. We want to consider two hypotheses ofG2 having two or three copies. Denote these two hypotheses by H2 (G2 hastwo copies) and H3 (G2 has three copies), respectively. Under theseassumptions, we can calculate the binomial parameter p for eachhypothesis and values of A₁, A₂, B₁, and B₂ as

$p = {\frac{{0.96*A_{1}} + {0.04*A_{2}}}{{0.96*A_{1}} + {0.04*A_{2}} + {0.96*B_{1}} + {0.04*B_{2}}}.}$

This gives us the following values for p (Table 2).

TABLE 2 Binomial parameter p values for different hypotheses and valuesof A₁, A₂, B₁, and B₂. Binomial Parameter p (A₁ = 0, (A₁ = 1, (A₁ = 2,B₁ = 2) B₁ = 1) B₁ = 0) H2 (A₂ = 0, B₂ = 2) 0 0.48 0.96 (A₂ = 1, B₂ = 1)0.02 0.5 0.98 (A₂ = 2, B₂ = 0) 0.04 0.52 1 H3 (A₂ = 0, B₂ = 3) 0 0.4710.941 (A₂ = 1, B₂ = 2) 0.196 0.490 0.961 (A₂ = 2, B₂ = 1) 0.039 0.5100.980 (A₂ = 3, B₂ = 0) 0.059 0.529 1

We further know that A is distributed bino(p·N) and that H has a Normaldistribution with mean p and variance p(1−p)/N. As the number of nucleicacid molecules increases, the variance of the distributions decreasesand the various hypotheses can be more easily distinguished. Forexample, given (A₁=1, B₁=1) and that we want to distinguish between H2and H3. For the sake of simplicity, we will reduce the problem todistinguishing between (A₂=1, B₂=1) and (A₂=2, B₁=1). The abovedeveloped model can be used to calculate the minimum number of nucleicacid molecules necessary to achieve a specific specificity andsensitivity (Table 3).

TABLE 3 Sequencing reads required for method 2 given various fractionsof G2 in the sample and different target sensitivities andspecificities. Target Sensitivity and Specificity 99.9% 99.8% 99.5% 99%98% 95% 90% 85% 80% Fraction 0.5%  6,142,300 5,328,183 4,267,5923,480,952 2,712,960 1,740,216 1,056,382 690,926 455,598 of G2 in  1%1,543,243 1,338,698 1,072,226 874,584 681,627 437,227 265,414 173,594114,468 the sample  2% 389,659 338,013 270,730 220,827 172,107 110,39767,015 43,831 28,903  3% 174,901 151,719 121,519 99,119 77,251 49,55230,080 19,674 12,973  4% 99,353 86,185 69,029 56,305 43,883 28,14817,087 11,176 7,369  5% 64,211 55,700 44,613 36,390 28,361 18,192 11,0437,223 4,763  6% 45,027 39,059 31,284 25,518 19,888 12,757 7,744 5,0653,340  7% 33,403 28,976 23,208 18,930 14,754 9,464 5,745 3,757 2,478  8%25,822 22,399 17,941 14,634 11,405 7,316 4,441 2,905 1,915  9% 20,59917,869 14,312 11,674 9,098 5,836 3,543 2,317 1,528 10% 16,845 14,61311,704 9,547 7,440 4,773 2,897 1,895 1,249 15% 7,848 6,807 5,452 4,4473,466 2,223 1,350 883 582 20% 4,622 4,009 3,211 2,619 2,041 1,309 795520 343 25% 3,094 2,684 2,150 1,753 1,367 877 532 348 229 30% 2,2451,948 1,560 1,272 992 636 386 253 167 35% 1,722 1,494 1,196 976 761 488296 194 128 40% 1,375 1,193 955 779 607 390 237 155 102 45% 1,132 982787 642 500 321 195 127 84 50% 955 828 663 541 422 271 164 107 71Practical Implications

Using the methods analyzed above and the efficiencies of samplepreparation and library preparation, it is possible to calculate, for aparticular sensitivity and specificity, the amount of sample required toobtain a specific number of unique sequencing reads. An exemplaryworkflow would be: sample collection→sample prep→library prep→hybridcapture→barcoding→sequencing. Based on this workflow, it is possible towork backwards to determine the sample requirements, given someassumptions about the efficiencies of each step. In this example, thebarcoding step is assumed to have no significant impact. If N uniquesequencing reads are required from a chromosome or chromosome segment,the preferred approach is to exhaustively sequence the nucleic acidmolecules. Results based on the Coupon Collector's Problem (for example,see Dawkins, Brian (1991), “Siobhan's problem: the coupon collectorrevisited”, The American Statistician, 45 (1): 76-82) can be used asguidance for how many sequence reads are necessary to have a particularprobability of having sequenced all the nucleic acid molecules. Seetable below. For example, if there are 1,000 unique tagged nucleic acidmolecules to be sequenced, a depth of read of approximately 12× isnecessary to have a 99% probability of observing all the nucleic acidmolecules. This estimate assumes that each sequence read is equallylikely to be anyone of the 1,000 tagged nucleic acid molecules. If thisis not the case, the calculated factor of 12 can be replaced with anempirically measured one. During the library prep and hybrid capturesteps, some of the sample nucleic acid molecules present in the bloodtube are lost. If we assume that 75% of molecules are lost in theseprocesses (i.e., 25% of the sample nucleic acid molecules are retained),more nucleic acid molecules are required in the original to be surethere are sufficient tagged nucleic acid molecules remaining forbarcoding. The binomial distribution can be used here to estimate thenumber of nucleic acid molecules in the sample necessary to have, with acertain probability, a particular number of nucleic acid molecules afterthe library and hybrid capture steps.

Based on the above reasoning, approximately 110,000 sequencing reads onboth the reference chromosome or chromosome segment and the chromosomeor chromosome segment of interest are necessary for 1% sensitivity andspecificity in a mixture with 4% of G2 using method 1 (Table 1). If thecombination of the library prep and hybrid capture steps has an overallefficiency of 25%, then more than 110,000 starting copies are needed inthe sample. Using a simple binomial model, at least 443,000 samplenucleic acid molecules are required to ensure a greater than 99% chanceof having at least 110,000 nucleic acid molecules available forbarcoding and subsequent sequencing. Assuming the library preparationbegins with 443,000 nucleic acid molecules, the expected number ofsample nucleic acid molecules will be in the range of 110,000 to 111,400molecules after the library prep and hybrid capture steps. To ensuremeasurement of all original molecules, the higher number can be used forfurther calculations, i.e., 111,400 nucleic acid molecules. Because ofthe variance in measuring nucleic acid molecules, to have a highprobability of measuring all the 111,400 nucleic acid molecules,substantially more measurements are required. For example, to have a 99%probability of sequencing all the tagged nucleic acid molecules, it isnecessary to sequence 16 times the number of nucleic acid molecules.Therefore, approximately 1,780,000 reads are required for eachchromosomes or chromosome segment. This estimate assumes that eachsequence read is equally likely to be any one of the 111,400 taggednucleic acid molecules. If this is not the case, the calculated factorof 16 can be replaced with an empirically measured one.

In terms of the sample, as stated before, about 443,000 total samplenucleic acid molecules are required to attain the previously statedperformance. The required 111,400 sequencing reads can be achieved bymeasuring multiple loci in each chromosome or chromosome segment. Forexample, if nucleic acid molecules at 1,000 different loci are measured,an average of about 112 unique nucleic acid molecules from each locusare required for sequencing, leading to an average of about 443 uniquenucleic acid molecules in the starting sample. If the underlying sampletype is a plasma sample from a human, it contains between 1,200 to 1,800single haploid copies of the genome per ml of plasma. Further, onaverage 1 ml of blood sample contains approximately 0.5 ml of plasma.Thus, given these constraints, 1 ml of blood (0.5 ml plasma and 600-900unique nucleic acid molecules from each locus) should be sufficient todetermine the copy number of a chromosome or chromosome segment ofinterest.

The MITs can be used to here to count individual sample nucleic acidmolecules and reduce the variance associated with other quantitativemethods. To simplify counting of individual sample nucleic acidmolecules, each sample nucleic acid molecule from a locus (i.e. each ofthe 443 nucleic acid molecules) should have a different combination ofattached MITs. Given two MITs are being attached to each nucleic acidmolecule, the number of possible combinations of attached MITs is N²,where N is the number of MITs in the set. As there are approximately 443copies of each locus, N² needs to be greater than 443. It is beneficialto have some buffer, so if N²=1,000, N would be approximately 32. It isalso possible to use the exact start and end genomic coordinates of thenucleic acid segment, in conjunction with the sequences of the MITs, toidentify sample nucleic acid molecules.

Those skilled in the art can devise many modifications and otherembodiments within the scope and spirit of the present disclosures.Indeed, variations in the materials, methods, drawings, experiments,examples, and embodiments described can be made by skilled artisanswithout changing the fundamental aspects of the present disclosures. Anyof the disclosed embodiments can be used in combination with any otherdisclosed embodiment. All headings in this specification are for theconvenience of the reader and do not limit the present disclosures inany way.

What is claimed is:
 1. A method of determining the number of copies ofone or more chromosomes or chromosome segments of interest from a targetindividual in a sample of blood, or a fraction thereof, from the targetindividual or from the mother of the target individual, the methodcomprising: forming a population of tagged nucleic acid molecules byreacting a population of sample nucleic acid molecules with a set ofnucleic acid molecular index tags (MITs), wherein the number ofdifferent MITs in the set of MITs is between 10 and 1,000, wherein aratio of the total number of sample nucleic acid molecules in thepopulation of sample nucleic acid molecules to the diversity of MITs inthe set of MITs is greater than 1,000:1, wherein at least some of thesample nucleic acid molecules comprise one or more target loci of aplurality of target loci on the chromosome or chromosome segment ofinterest, and wherein the sample is 1.0 ml or less of blood or afraction of blood derived from 1.0 ml or less of blood; amplifying thepopulation of tagged nucleic acid molecules to create a library oftagged nucleic acid molecules; determining the sequences of the attachedMITs and at least a portion of the sample nucleic acid segments of thetagged nucleic acid molecules in the library of tagged nucleic acidmolecules, to determine the identity of a sample nucleic acid moleculethat gave rise to a tagged nucleic acid molecule; measuring a quantityof DNA for each target locus by counting the number of sample nucleicacid molecules that comprise each target locus using the determinedidentities; and determining, on a computer, the number of copies of theone or more chromosomes or chromosome segments of interest using thequantity of DNA at each target locus in the sample nucleic acidmolecules.
 2. The method of claim 1, wherein the number of target lociand the volume of the sample provide an effective amount of total targetloci to achieve a desired sensitivity and a desired specificity fordetermining the number of copies.
 3. The method of claim 2, wherein theplurality of target loci comprises 1,000 target loci and wherein thesample is plasma.
 4. The method of claim 2, wherein the total number ofMIT molecules in the reaction mixture is greater than the total numberof sample nucleic acid molecules in the reaction mixture, wherein thepopulation of tagged nucleic acid molecules is formed using a ligationreaction, wherein the population of tagged nucleic acid molecules isenriched using hybrid capture before the amplifying, and wherein thenumber of total target loci in the sample is at least 4 times greaterthan the number of total target loci required to meet the desiredspecificity and the desired sensitivity.
 5. The method of claim 2,wherein the number of target loci and the volume of the sample provideat least 500,000 total target loci in the sample, wherein the set ofMITs comprises at least 32 MITs, wherein the sample is from the motherand comprises at least 3% fetal nucleic acids compared to maternalnucleic acids, and wherein the desired specificity is 99% and thedesired sensitivity is 99%.
 6. The method of claim 5, wherein the sampleis 0.5 ml or less of blood or the sample is a fraction of blood derivedfrom 0.5 ml or less of blood.